- 
- 
-
-
-The top of the left hand dialog box should always give you an idea about the next steps in basic tracing of paths. However, the first step when you load a new image should probably be to enable the option for using Hessian-based analysis of the image - this is done via a checkbox a little further down the dialog box. It will take some time to calculate the Gaussian convolution of the image once you select this option, but this only needs to be done once per image, so it's best to do it at the start. There is more on the use of this option in the [Tips](#miscellaneous-tips) section below.
-
-*At this point, you may wish to switch to some shorter [step-by-step](/plugins/simple-neurite-tracer/step-by-step-instructions) instructions - some people have suggested that the description below is a bit verbose. Alternatively, carry on below...*
-
-Now, as the instructions suggest, your next step should be to click on the point in the image stack where you want to start the path. To navigate in the stack you would adjust the slices scroll bar or used the {% include key key='<' %} and {% include key key='>' %} keys as usual. The red cross-hairs indicate the corresponding position in the three different views of the stack, but the slice positions will not be synchronized between the three windows unless you hold down {% include key key='Shift' %} while moving the mouse or activate the *Enable cursor snapping* option (window synchronization is particularly useful if you're creating a [branching branch](#branching-and-joining-paths) at the beginning or end of a path).
-
-   Select a point for the start of your first path. The instructions should change to prompt you to find another point further along the structure that you're tracing. It will take some trial and error to find out how far apart these points can be for each image - some will have very clearly defined neurons and so they can be very far apart, but with more difficult images (or ones where the path found is not the one you intend) you will need to make them closer together.
-
-Once you select that next point in the path you will either find that the path is found immediately, in which case the projected path is visible as a dark blue line, or the search may take longer, in which case the progress of the search is shown in light blue.
-
-While the plugin is searching you can still move about in the image stack to see the progress through the depth of the stack as well. If it seems to be taking a very long time to find a path between the points you should probably cancel the search (by pressing {% include key key='Esc' %}) and try a point that's nearer, since the path searching slows down as it has explored more of the image.
-
-Once you have a dark blue temporary path like that in the left hand image the instructions will prompt you to either keep that path segment (by pressing {% include key key='Y' %}) or cancel it ({% include key key='N' %}) to try picking another point (probably one nearer to the original point). If you confirm that path then the path will turn red, to indicate that this is a confirmed part of the current path. If you click further along the structure again then the dark blue colour will again show the temporary part of a path as opposed to the red confirmed part.
-
-Once you have picked out a few more points along the path, you can complete the path by clicking "Complete Path" {% include key key='F' %} at the top of the dialog. By default - Paths can be colorized at any later point using the drop-down menu in the *Paths* window - completed paths are shown in magenta and appear in the path list in the tracer's dialog box. If you select one or many paths in this list, the selected paths are shown in green instead. (You need to have particular paths selected for filling out neurons or branching and joining paths.) 
-
-You've probably noticed that the default presentation of the paths in an image is to show the a projection of the path through the entire stack, rather than just those points of the path that are in the current slice. This can become confusing with many paths in a single image, in which case you should change the *View Paths 2D* option from *Projected through all slices* to *Parts in nearby slices* (shortcut: {% include key key='5' %}).
-
-#### Branching and Joining Paths
-
-In this plugin each path can only be a linear succession of points in the image. However, you can indicate more complex structures by creating a path that starts on another path (branches off it) or ends on another path (joins the other path). To do this you have to select the existing path you want to branch off or join to in the path list (check that the right path is green in the image) and then hold down {% include key key='Ctrl' %} (on Windows or Linux) or {% include key key='option' style='mac' %} (on MacOS) while you select the branch or join point. You almost always will want to hold down {% include key key='Shift' %} as well as {% include key key='Ctrl' %} / {% include key key='Alt' %} while you're finding this image so that the crosshairs show you the exact point that you're joining to. The detailed procedure is described [here](Simple_Neurite_Tracer__Step-By-Step_Instructions#branching-start-a-path-on-an-existing-path).
-
-#### Saving and Loading Files
-
-You can load and save traces files with the corresponding buttons at the bottom of the tracer's dialog box. I suggest that you save your files with the original filename with the extension changed to ".traces", so "test.tif" would have a traces file "test.traces". This is because the "Load Traces File" option will look for a file with that name and offer to load it for you.
-
-#### Filling Out Neurons
-
-There is a simple facility in this plugin for "filling out" paths to volumes. This is not particularly sophisticated, but often good enough for a rough visualization of the shape of a neuron beyond what can be seen from the traced path.
-
-First, select the one or more paths that you want to fill out from in the path list and select "Fill Out Path(s)" in the interface. The selected paths are shown in green so that you can check that you're starting from the right ones. After a couple of seconds if you scroll through the stack you should be able to see a thick green suround to the path:
-
-
-
-The filler continues to explore the image starting from the path until you click "Pause" in the dialog. However, the fill which is shown only includes those points up to a certain threshold distance from the path. (Note that in this section "distance" doesn't mean a real physical distance, but a measure which takes into account the intensity values of the pixels which must be passed through when moving away from the path.) Information about the current threshold and the progress of the search is shown in the dialog. 
-
-The top line ("Not reached by search yet") is updated as you move your mouse over the image. If the point under the mouse has been reached by the search then it will show you that point's distance from the path. In the line below, the input box shows your current threshold distance: so if this is set to 0.2 then that means that all points less than 0.2 from the path are included in the fill (and shown in green in the image.) The number in parentheses at the right of this line show the maximum distance from the path that has been completely explored.
-
-You can change the fill threshold in one of three ways:
-
-- Clicking on a point in the image that has been reached by the search (This is the most intuitive way of altering the threshold).
-- Changing the threshold in the input box manually and clicking the "Set" button below it.
-- Clicking the "Set Max" button below the threshold input box, which sets the threshold to the maximum explored distance (the value shown in parentheses).
-
-Anyway, assuming that you want to use the first of these approaches, you should use the approach described below. It is difficult to set the threshold accurately from the image unless you zoom in, so first zoom on part of the path that you want to set the threshold for: 
-
-{% include clear%}
-
-
-Since the the solid green fill obscures the intensity value of the points in the fill, I suggest that you switch to the semi-transparent view of the fill at this stage by selecting the "Transparent fill display" option in the dialog. This should show you something like this:
-
-
-
-{% include clear%}
-
-
-As you can see in this image, the threshold is set too far from the path, since there are many completely dark points under the green fill. Experiment with clicking on different points closer to the path in order to adjust the threshold until you are happy with it. You might end up with something like this:
-
-
-
-{% include clear%}
-
-
-If you are happy with this, then you might as well click "Pause" so that your computer isn't spending all its CPU on continuing to explore the image. Then you can either save the fill (which will add it to the fill list) by clicking "Save Fill", discard the fill by clicking "Cancel Fill" or use the "Create Image Stack from Fill" button to view the same image stack, but with only the points in that fill preserved. One reason why you might want to do this is that you can then smooth that image and use the [3D Viewer](/plugins/3d-viewer) to do a surface rendering of the neuron. Perhaps then you could overlay that onto a volume rendering of the complete image (see available [tutorials](/plugins/snt#tutorials)). Or, you could save those fill stacks for each of the neurons you fill and then combine them in ImageJ using "RGB Merge".
-
-The image stack you would get from the image used in this example might look something like this: 
-
-{% include clear%}
-
-
-#### Using an AmiraMesh Labels File
-
-If you have a labels file for your image, you can load that file to help you make sure that your tracings are going between the regions of the image that you think they are. (e.g. it's possible when a neuron enters a region of dense expression to stop the path short of the regions which is actually labelled as a particular neuropil region.) Load the label file by clicking the "Load Labels" button. If you have a label file loaded then the current material under the crosshairs will be shown in the ImageJ status bar.
-
-#### Key Shortcuts
-
-Key Shortcuts and keyboard accelerators are described in [Key Shortcuts](/plugins/snt/key-shortcuts).
-
-#### Miscellaneous Tips
-
-- The simplest way to follow a path through a stack is to select that path and hold down {% include key key='Ctrl' %} / {% include key key='Alt' %} and {% include key key='Shift' %} while moving the mouse along it.
-- If the search doesn't seem to be finding the route you expect through an image stack, try toggling the "Hessian analysis" option. Another alternative is that the start point of the search is in the wrong place (e.g. if you accidentally clicked in the image when you didn't want to start a new path - you should be able to tell this from the progress of the search, which starts at both the start and end point).
diff --git a/_pages/plugins/simple-neurite-tracer/export-to-swc-tutorial.md b/_pages/plugins/simple-neurite-tracer/export-to-swc-tutorial.md
deleted file mode 100644
index 385292b72f..0000000000
--- a/_pages/plugins/simple-neurite-tracer/export-to-swc-tutorial.md
+++ /dev/null
@@ -1,59 +0,0 @@
----
-mediawiki: Simple_Neurite_Tracer:_"Export_to_SWC"_Tutorial
-title: Simple Neurite Tracer › "Export to SWC" Tutorial
-nav-links: true
-nav-title: Exporting to SWC
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-This short tutorial shows you how to export a connected set of paths in the [Simple Neurite Tracer](/plugins/snt) plugin to an SWC file. This may be useful for analyzing a structure in other tools (e.g. [L-measure](http://cng.gmu.edu:8080/Lm/)) or uploading to a database like [NeuroMorpho.org](http://neuromorpho.org/). (n.b. for use in L-measure you will have to set the SWC type for each path - see [\#Setting\_the\_SWC\_point\_types](#setting-the-swc-point-types))
-
-## Export all connected path sets as SWC files
-
-To export each connected set of paths as a separate SWC file, you can now select the "Export all as SWC..." menu option - you will be prompted for the prefix of the file names:
-
-{% include img align="center" src="save-all-as-swc" %}
-
-## Export a single connected path set as an SWC file
-
-Often, you will just want to export one set of connected paths. As an example of this, suppose we have a partially traced image like this:
-
-{% include img align="center" src="export-to-swc-tutorial-1" width="750" %}
-
-Those are actually three disconnected groups of paths, as you can see from the path list:
-
-{% include img align="center" src="export-to-swc-tutorial-2" %}
-
-In other words, there is one large group of neurons which are all connected, with "Path (0)" as the primary path, there is a single disconnected path ("Path (15)" and group of 6 paths with "Path (16)" as the primary path.
-
-(Paths are connected when you start one path on another one (branching) or end one path on another one (joining). To find out how to do that, see the [Simple Neurite Tracer: Step-By-Step Instructions](/plugins/simple-neurite-tracer/step-by-step-instructions).)
-
-The SWC file format describes a single neuron's morphology (so every point is connected to another one), whereas a .traces file in Simple Neurite Tracer can describe multiple disconnected structures. This means that in this plugin you can only export a complete connected set of paths to SWC. So, in this example, you could only export three different SWC files, since there are three connected groups of paths. To do that, select all of the paths in that structure (using {% include key key='Shift' %} or {% include key key='Control' %} when selecting items in the list) - that should look like this:
-
-{% include img align="center" src="export-to-swc-tutorial-3" %}
-
-... and then click the "Export to SWC" button in the bottom right of that window. If you haven't selected a completely connected set of paths, then you will get an error at this point - otherwise you will be prompted to save the SWC file.
-
-### Setting the SWC point types
-
-There is now support in Simple Neurite Tracer for setting the type of SWC points contained in each path. You can do this by selecting a set of paths and then choosing a value from the SWC Type context menu:
-
-{% include img align="center" src="snt-set-to-soma" %}
-
-You can set each path to a different type in this way, e.g.:
-
-{% include img align="center" src="snt-after-setting-swc-types" %}
-
-Note: setting an SWC type for every point is **required** by some software, such as L-measure.
-
-### Further Notes
-
-- You should only export your tracings to SWC for analysis in other tools, or or for uploading to databases that require that format. The SWC format is very simple and you lose a lot of information if you don't save your tracings in the plugin's native format.
-
-
-
-- The root node in an exported SWC file will be the first point in the primary path of the group in Simple Neurite Tracer. So, if you care about this, then before saving you should pick the path in the group which starts with what you consider to be the root node, and click "Make Primary" in the Path Window before exporting.
-
-
diff --git a/_pages/plugins/simple-neurite-tracer/index.md b/_pages/plugins/simple-neurite-tracer/index.md
deleted file mode 100644
index 7644e06d9f..0000000000
--- a/_pages/plugins/simple-neurite-tracer/index.md
+++ /dev/null
@@ -1,15 +0,0 @@
----
-title: Simple Neurite Tracer
-nav-links: true
-nav-title: Index
-categories: [Uncategorized]
-doi: 10.1093/bioinformatics/btr390
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-The Simple Neurite Tracer plugin was designed to allow easy semi-automatic
-tracing of neurons or other tube-like structures (e.g. blood vessels) through
-3D image stacks. It has been replaced by the much more sophisticated
-[SNT](/plugins/snt) plugin.
diff --git a/_pages/plugins/simple-neurite-tracer/preprocessing-data-for-better-results.md b/_pages/plugins/simple-neurite-tracer/preprocessing-data-for-better-results.md
deleted file mode 100644
index db7f350b2f..0000000000
--- a/_pages/plugins/simple-neurite-tracer/preprocessing-data-for-better-results.md
+++ /dev/null
@@ -1,59 +0,0 @@
----
-mediawiki: Simple_Neurite_Tracer:_Preprocessing_Data_for_Better_Results
-title: Simple Neurite Tracer › Preprocessing Data for Better Results
-nav-links: true
-nav-title: Preprocessing Data
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-Simple Neurite Tracer's "Hessian-based analysis" option for filtering for tube-like structures is an quick way of improving the efficiency and accuracy of path-finding. However, for best results, I would recommend using a slower but more accurate method to preprocess the data.
-
-## Using Pre-Processed Data
-
-If the file you are tracing was originally called "example.tif" or "example.lsm", then the plugin will check for the existence of a file in the same directory called "example.tubes.tif". If such a file exists, the plugin will offer to load it for you:
-
-
-
-The "\*.tubes.tif" file must be a 32-bit float image. Then, if you select the "Use preprocessed image" option:
-
-
-
-... then tracing will take place on the preprocessed image rather than the raw image data or the "Hessian-based analysis" filtered values.
-
-## An Example Using Frangi et al.'s method
-
-### A single image
-
-To process a single image, load your image ("test.lsm", say) into Fiji and select {% include bc path='Plugins | Process | Frangi Vesselness'%}. (There is more information about this plugin [on its page](/plugins/frangi).) By way of example, let's say that you select 4 scales from half the x voxel separation to twice that value.
-
-Then save that file in the same directory as "test.tubes.tif".
-
-When you start up Simple Neurite Tracer with "test.lsm" as the current image, it will offer to load the preprocessed image you have just generated.
-
-### Preprocess Multiple Images
-
-The easiest way to preprocess multiple images is to record a macro for processing a single images, and then wrap it it in a loop to iterate over all the files in a directory. For example:
-
-```javascript
-d = getDirectory("Select a directory");
-files = getFileList(d);
-
-extension = ".tif";
-
-for( i = 0; i < files.length; ++i ) {
- filename = files[i];
- if( endsWith(filename,extension) ) {
- l = lengthOf(filename);
- el = lengthOf(extension);
- basename = substring(filename,0,l-el);
- expected_window_name = "vesselness of "+filename;
- output_filename = d + File.separator + basename + ".tubes.tif";
- open(filename);
- run("Frangi Vesselness (imglib, experimental)", "number=1 minimum=0.288387 maximum=0.288387");
- selectWindow(expected_window_name);
- saveAs("Tiff", output_filename);
- }
-}
-```
diff --git a/_pages/plugins/simple-neurite-tracer/screencasts.md b/_pages/plugins/simple-neurite-tracer/screencasts.md
deleted file mode 100644
index f8dc797c16..0000000000
--- a/_pages/plugins/simple-neurite-tracer/screencasts.md
+++ /dev/null
@@ -1,30 +0,0 @@
----
-mediawiki:
-- Simple_Neurite_Tracer:_Introductory_Screencast
-- Simple_Neurite_Tracer:_Old_Screencast1
-- Simple_Neurite_Tracer:_Old_Screencast2
-- Simple_Neurite_Tracer:_Old_Screencasts
-title: Simple Neurite Tracer › Screencasts
-nav-links: true
-nav-title: Screencasts
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-This screencast (which needs audio) explains basic use of the plugin. It
-probably won't be clear what's going on unless you make it full-screen:
-
-{% include video platform="youtube" id="y6ZPdDfUOjI" width=420 %}
-
-## Older screencasts
-
-These screencasts are from very early versions of the plugin, but may still be of some use since all the functionality is still present.
-
-This first screencast shows the basic operation of the plugin on a fairly indistinct confocal scan. After about a minute I turn on the option to use a Hessian-based cost function for the search, based on code written by Stephan Preibisch at the Janelia Farm Hackathon. You may notice that the searches after that point follows the neurons more closely. However, in some cases that finds erroneous paths or the naive cost function performs better, so in practice one switches back and forth. \[Note that this demo was recorded from an earlier version that didn't have support for branching.\]
-
-{% include video platform='youtube' id='SSXx3DLCJD8'%}
-
-This next video demonstrates more of the functionality that I added at Janelia Farm, in particular the fitting of centre lines and the filling-out of neurons. I use Benjamin Schmid's [3D Viewer](/plugins/3d-viewer) in this demo for visualizing the results, and as an example export the mesh and load it into Blender at the end - thanks to Albert Cardona for his advice on all matters Blender.
-
-{% include video platform='youtube' id='sjSsNsr_2YM'%}
diff --git a/_pages/plugins/simple-neurite-tracer/selecting-paths.md b/_pages/plugins/simple-neurite-tracer/selecting-paths.md
deleted file mode 100644
index 84c38d66cf..0000000000
--- a/_pages/plugins/simple-neurite-tracer/selecting-paths.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-mediawiki: Simple_Neurite_Tracer:_Selecting_paths
-title: Simple Neurite Tracer › Selecting paths
-nav-links: true
-nav-title: Selecting Paths
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-There are three ways of selecting a particular path in [Simple Neurite Tracer](/plugins/snt).
-
-### In the Path Window
-
-You can select a path in the Path Window. You can also use the up and down cursor keys to go through the list quickly, and see which paths turn green in the 2D and 3D tracing views.
-
-### In the 2D tracing view
-
-If you press the {% include key key='G' %} key with your mouse over a path in the 2D tracing view, that path should be selected. Note that this is the nearest path to the point shown in the image, so if you're showing paths projected through all slices, this may not be the one you expect. You can make this more obvious by switching the 'View paths (2D)' option to 'parts in nearby slices'. Alternatively, just move through the stack to a nearby slice before pressing {% include key key='G' %}.
-
-### In the 3D tracing view
-
-There are various ways to select a path in the 3D viewer, from easiest to most difficult:
-
-- If you press {% include key key='G' %} when the mouse is over a path in the 3D Viewer, it will be selected.
-
-
-
-- If you select a path in the 3D viewer, it should now also be selected in the rest of the tracing interface. One way of doing this is via the "Select" menu.
-
-
-
-- Alternatively, you can click on the path in the 3D view. Note that you will probably have the problem that clicks in the 3D view only select the volume rather than the paths - you can get around this by selecting the volume and then unticking {% include bc path='Edit | Hide/Show | Show content'%} to hide the volume rendering. Then clicking on the paths will be easy.
diff --git a/_pages/plugins/simple-neurite-tracer/sholl-analysis.md b/_pages/plugins/simple-neurite-tracer/sholl-analysis.md
deleted file mode 100644
index 0e4947468b..0000000000
--- a/_pages/plugins/simple-neurite-tracer/sholl-analysis.md
+++ /dev/null
@@ -1,57 +0,0 @@
----
-mediawiki: Simple_Neurite_Tracer:_Sholl_analysis
-title: Simple Neurite Tracer › Sholl Analysis
-nav-links: true
-nav-title: Sholl Analysis
----
-
-{% include notice icon="warning" content='This is an old tutorial on how to call the [Sholl Analysis](/plugins/sholl-analysis) plugin from [Simple Neurite Tracer](/plugins/snt). **It is rather outdated. More up-to-date information is provided in [SNT: Analysis](/plugins/snt/analysis#sholl-analysis).** For an overview of the technique refer to the [Sholl Analysis](/plugins/sholl-analysis) documentation page.' %}
-
-# Introduction
-
-This tutorial assumes that you've already traced an image with Simple Neurite Tracer (SNT) and that you are familiar with the [variants of Sholl methods](/plugins/sholl-analysis#methodstable) and the [Sholl Analysis](/plugins/sholl-analysis) plugin. This tutorial will use an olfactory projection fibre image, freely available from the [Diadem challenge data set](http://www.diademchallenge.org/olfactory_projection_fibers_readme.html).
-
-# Retrieving Profiles
-
-When you've loaded the traces, that should look something like this: 
-
-Now you have to pick a centre point for the analysis. This might be the soma or a [relevant focal point](http://forum.imagej.net/t/sholl-analysis-validation-parameters/3065/2). The centre point must be on one of your existing paths. First, select the path on which your centre point lies: 
-
-Now hold down {% include key keys='Ctrl|Shift' %} (on Windows or Linux) or {% include key keys='option|shift' style='mac' %} (on Mac) and move the mouse along the path. A red cross-hair should track along the path: 
-
-... when you've got the red cross-hairs at a suitable point, still holding down {% include key key='Ctrl' %} / {% include key key='Alt' %} and {% include key key='Shift' %}, press the {% include key key='A' %} key. Then you can release the other keys. You should see the Sholl analysis interface appear like this: 
-
-Consider the first two options: you should probably select the top option *Use all N paths in analysis?* unless you're only wanting to include a subset of the paths, for example if your image stack contains multiple separate neurons. Next you can click on *Plot Profile* so that you can visualize how the intersections with concentric spheres vary with distance from your centre point: 
-
-This graph shows exactly how many times a sphere of a particular radius will intersect with paths (i.e., *continuos sampling*). To consider spheres of evenly spaced radii (see definition of [Step size](/plugins/sholl-analysis#stepsize)), you have to enter a value into the *Radius step size* box. E.g., 
-
-# Data Normalization
-
-If you need to preview the effect of [normalizing](/plugins/sholl-analysis#methodstable) the number of intersections by the volume (or area) enclosed by the sphere (or circle) - you can do that by selecting the *Normalize for volume enclosed by circle* option: 
-
-The *Use standard axes* / *Use semi-log axes* / *Use log-log axes* controls whether the analysis is based on the log of normalized intersections and distance (*log-log*), the log of normalized intersections (*semi-log*) or unmodified values (linear axes) (see [Sholl Plots](/plugins/sholl-analysis#sholl-plots) for details. Note that the [Regression coefficient](/plugins/sholl-analysis#sholldecay) is always calculated in real time even if no normalization options are chosen.
-
-# Exporting Profiles
-
-You can export profiles by clicking on "Save Profile" which will prompt for a CSV filename to save to. If you want to export the profile, so that you can edit in some other software or include it in a presentation, you can select *Export graph as SVG* in the graph window. You can then load the SVG file (e.g., in Inkscape):
-
-
-
-If you go back to the main tracer interface, keeping that *Sholl image stack* open, you can visualize those colours on the traces by switching the *Use colors / labels from* option to *Sholl analysis of all paths* (volume of original image made transparent for clarity): 
-
-
diff --git a/_pages/plugins/simple-neurite-tracer/step-by-step-instructions.md b/_pages/plugins/simple-neurite-tracer/step-by-step-instructions.md
deleted file mode 100644
index 8b30ede1f2..0000000000
--- a/_pages/plugins/simple-neurite-tracer/step-by-step-instructions.md
+++ /dev/null
@@ -1,63 +0,0 @@
----
-mediawiki: Simple_Neurite_Tracer:_Step-By-Step_Instructions
-title: Simple Neurite Tracer › Step-By-Step Instructions
-nav-links: true
-nav-title: Step-By-Step Instructions
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-# Step-by-Step Tracer Instructions
-
-These "step-by-step" instructions below assume that you have done the preliminary steps described on the [Simple Neurite Tracer: Basic Instructions](/plugins/simple-neurite-tracer/basic-instructions) page including starting up the plugin and turning on "Hessian-based analysis". Note that the screenshots here are from an early pre-release version of the plugin. The path list in the current version is in a separate window, but otherwise the interface is the same.
-
-## Trace a basic path:
-
-### 1. Pick a start point
-
-Before you pick a start point for your first path, the tracer will look like this:  Move through the image stack to find the start point of a path, then click there with the left mouse button.
-
-### 2. Click a subsequent point
-
-A small blue square should appear, showing the start of the path:  Move through the stack to find a subsequent point further along the same neuron, blood vessel, or whatever, and click there. During tracing, if a part cannot be found immediately, you may see the progress of the search in cyan:  You can scroll through the stack while such a search is in progress - if it appears not be making good progress, it's probably best to click "Abandon search" (or press {% include key key='Esc' %}) and pick a point closer to the start point.
-
-### 3. Confirm the temporary path
-
-Once the search has found that point, it is shown in blue (to indicate that this is still a temporary path) and you are asked to confirm (by clicking "Yes" or pressing {% include key key='Y' %}) that this path is following the route through the stack that you expect. If it is not, then click "No" {% include key key='N' %} and you'll go back to step 2. 
-
-### 4. After confirming the temporary path
-
-Assuming you confirmed the path, the confirmed path will appear in red, like this:  Now you are essentially back at step 2. Normally you will go on top pick further points along the structure. However, if you have finished with that path, click "Finish Path" {% include key key='F' %} and you will go back to step 1.
-
-### 5. After completing a path
-
-If you completed that path it will be shown in magenta: 
-
-## Branching: Start a path on an existing path
-
-Before you pick a start point for your first path, the tracer will look like this: (We've zoomed in on the region of interest) 
-
-### 1. Select the path to branch off
-
-To select the path you want to branch off from, you can either select it in the path list, or press {% include key key='G' %} while your mouse pointer is over the path. When the path is first selected, it will be shown in the default green color, as below: 
-
-### 2. Click while holding the branch modifier to start the branch
-
-To force the start of the new path to be a branch off the selected path, hold down the {% include key keys='Ctrl|Shift' %} keys while you move the mouse to find the right point under the red cross-hairs. Then click with the left mouse button - {% include key keys='Ctrl|Shift' %} should still be held down. Finally release the keys. **N.B. on MacOS you must use {% include key keys='Alt|Shift' %} instead.** Once you've started a path, it looks like this: 
-
-### 3. Continue adding to the path as normal
-
-From this point on, you can carry on adding to the path as above, e.g. create a temporary path:  ... and confirm it:  When you decide to complete the path you should see in the path list that it has been recorded as starting on the existing path: 
-
-## Joining: End a path on an existing path
-
-Supposing you want the end of a path that you're tracing to join onto an existing path, you just use the same modifier key when selecting the end point of the last part of the path. To go into that in more detail, if you're half way through tracing a path like this: 
-
-... and you want the final part of that path to join up with the existing path running from the bottom to the top of the image. First, select that path in the path list, so that it turns green: 
-
-Now hold down {% include key keys='Ctrl|Shift' %} (or {% include key keys='Alt|Shift' %} on MacOS) to restrict the end point to be a "join" on that existing path. Click (while still holding down the modifier keys) to start the search for that end point and make it join the existing path. If the search can find a path to the end point, the result should look like this: 
-
-If you're happy with that, confirming the temporary path will automatically complete the whole path, since if you're creating an end join there cannot be any more to the path. The result will look like this: 
-
-Note that the path list indicates that this new path (1) ends on the existing one (0).
diff --git a/_pages/plugins/simple-neurite-tracer/testing-procedure.md b/_pages/plugins/simple-neurite-tracer/testing-procedure.md
deleted file mode 100644
index 5e1980d411..0000000000
--- a/_pages/plugins/simple-neurite-tracer/testing-procedure.md
+++ /dev/null
@@ -1,141 +0,0 @@
----
-mediawiki: Testing_Procedure_for_Simple_Neurite_Tracer
-title: Simple Neurite Tracer › Testing Procedure
-nav-links: true
-nav-title: Testing Procedure
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-This is a set of instructions to follow to test as much of the code as possible in [Simple Neurite Tracer](/plugins/snt). It does not give complete coverage, but following this before each new release should stop the more obvious problems from getting through. The coverage results for this procedure with VIB at 6840872c6a492e31caa453a6776d1e9fac26f58d are [here](https://fiji.sc/~longair/coverage-VIB-6840872c6a492e31caa453a6776d1e9fac26f58d/_files/2b.html).
-
-## Basic Tracing
-
-- Open example-for-tracing.tif
-- Run "Simple Neurite Tracer", selecting "Create new 3D Viewer" and "Use three pane view"
-- Rotate the 3D view
-- Use the slice selector to run through the slices in each pane
-- Hold down Shift while moving the red crosshair around in each pane in turn
-- Click to start a path
-- Cancel Path
-- Click to start a path
-- Select a further point along the path
-- Check with "Shift" that the cyan search progress appears in each pane
-- Check that blue path is create in each pane, and in the 3D viewer
-- Click "No" to answer the question "Keep new path segment"
-- Try again to select a further point along the path
-- Click "Abandon Search" half way through the search for the path.
-- Try again to select a further point along the path, but allow it to continue to completion
-- Click "Yes" to confirm the temporary path
-- Check that the red path appears in all panes and the 3D viewer
-- Pick a further point and confirm that next segment.
-- Click on "Complete Path"
-- Check that the magenta path appears in all of the viewers
-- Select the path in the Path Window
-- Hold down Control and click a point on the existing path where you want a branch point to start
-- Add a few more segments to the the new path, complete it normally
-- Start a new path at a random point in the stack, and end it on an existing path by holding down Control when you select the final point
-- Create a new path that both starts and ends on an exisiting path
-- Check that these paths appear sensibly in the Path window
-- Try selecting and deselecting the paths in the Path window, check that the right paths are highlighted in each pane and in the 3D viewer
-- Turn on the "Only Show Selected Paths" option and do the same, checking that only the selected paths appear
-- Turn off the "Only Show Selected Paths"
-- Select "2D: parts in nearby slices"
-- Look through all the slices to check that they're displayed properly
-- Try changing the "slices on either side" parameter and doing the same
-- Turn on "Hessian based analysis"
-- Add an extra path
-- Turn off "Hessian based analysis"
-- Click on "Pick Sigma Visually"
-- Click on an interesting point in the image
-- In the Sigma Palette, try adjusting the maximum, adjusting the slice and click on one of the boxes with a different sigma
-- Close the palette and wait for the Gaussian to finish calculating
-- Try adding a path
-- Turn off "Hessian based analysis"
-- Click "Pick Sigma Visually", click in the image, but close the window while the palette is generating to check that this cancels the generation properly
-- Click "Pick Sigma Manually" and try setting some values - check that the Gaussian is recalculated and you can trace a new path
-- Click on the green rectangle and then change the colour. Check that the colour changes in the panes and in the 3D Viewer
-- Click on the magenta rectangle and then change the colour. Check that the colour changes in the panes and in the 3D Viewer.
-- Use "Show / Hide Fill List" and "Show / Hide Path List" to display and hide the two windows
-- Select a single path in the Path Window, hold down Shift and click "Fit Volume"
-- "Fly Through" the normal path which is fitted
-- Select all paths in the Path Window and click "Fit Volume"
-- Check that they are all fitted in the 3D Viewer (note bug here: selection is not preserved afterwards)
-- Try selectively unfitting two of the paths
-- Refit one of them.
-- Select a (not top level path) and click "Make Primary"
-- Check that the path list is rearranged
-- Click on a path and rename it (not bug here: only the non-fitted path's name is changed)
-- Delete the path with start and end joins
-- Don't quit the tracer but move onto the next set of tests...
-- Select a single path and click "Fill Out" (note bug here: panes stop updating due to NPE)
-
-```
-Exception in thread "AWT-EventQueue-0" Exception in thread "AWT-EventQueue-0" java.lang.NullPointerException
- at tracing.SearchThread.anyNodeUnderThreshold(SearchThread.java:682)
- at tracing.SearchThread.drawProgressOnSlice(SearchThread.java:729)
- at tracing.FillerThread.drawProgressOnSlice(FillerThread.java:365)
- at tracing.TracerCanvas.drawOverlay(TracerCanvas.java:87)
-```
-
-- (FIXME: add further filling test script here.)
-- Click "Cancel Fill"
-- Move on to the next section
-
-## Saving and Loading
-
-- Click "Export as CSV"
-- Check that the CSV file has been created properly
-- Repeat, checking there's a warning about overwriting and overwriting
-- Repeat, checking there's a warning about overwriting and not overwriting
-- Click "Save Traces File", save to foo.nonstandard
-- Quit the tracer (there should be no "unsaved paths" warning...)
-- Close the 3D Viewer
-- Start "Simple Neurite Tracer" and select "Create new 3D Viewer" and "Three Pane View"
-- Click "Load Traces" and select foo.nonstandard
-- Look through the stack and check that all are reloaded, the renamed path is still renamed, etc.
-- Add a new path
-- Click "Quit Tracer", check that you're warned about unsaved paths - cancel, check that it doesn't quit
-- Click "Quit Tracer", check that you're warned about unsaved paths - go ahead and quit
-- Rename "foo.nonstandard" to "foo.traces"
-- Start "Simple Neurite Tracer" and select "Create new 3D Viewer" and "Three Pane View"
-- Click "Load Traces" and check that it offers to load the renamed traces file.
-- Click "No", and select it manually.
-- Quit the tracer and try again, this time loading the default when it offers.
-
-## Test Different 3D Views
-
-- Load up the traces file, make sure that some paths are fitted, some not
-- Try each of the View Paths (3D) options, check they all work
-- Change back to surface reconstructions
-
-## Reuse an existing 3D viewer
-
-- Select "Show only selected paths", pick two fitted paths
-- Change the fitted path colour to something different from the default (e.g. yellow)
-- Quit the tracer, don't save
-- Select the "image for tracing" in the 3D Viewer, remove it
-- With the original ImagePlus as the current image, start the 3D viewer, but select "Reuse 3D Viewer", and pick the existing 3D Viewer
-- Add a new path, check that the existing yellow reconstructions are still there
-- Quit the tracer and close the 3D Viewer
-
-## Load Labels
-
-- Load up an image which has a corresponding labels file
-- Click "load labels", select the right labels file
-- Hover the mouse over different regions and check that the ImageJ status updates to tell you the region's name
-- Quit the tracer
-
-## Show Correspondences To Traces
-
-- Load a file for which you have a traces file
-- Start the tracer
-- Draw a few paths
-- Click "Show Corresponding Traces" and select the existing traces file
-- Change 3D view to "lines" and check that the correspondences are shown correctly
-- Quit the tracer
-
-## SWC Import
-
-- Load an image file for which you have a corresponding SWC file
diff --git a/_pages/plugins/simple-neurite-tracer/using-mip-overlays.md b/_pages/plugins/simple-neurite-tracer/using-mip-overlays.md
deleted file mode 100644
index d381c55f4a..0000000000
--- a/_pages/plugins/simple-neurite-tracer/using-mip-overlays.md
+++ /dev/null
@@ -1,18 +0,0 @@
----
-mediawiki: Simple_Neurite_Tracer:_Using_MIP_Overlays
-title: Simple Neurite Tracer › Using MIP Overlays
-nav-links: true
-nav-title: Using MIP Overlays
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-If you are tracing bright neurons with a structure that appears clear when viewed in a Maximum Intensity Projection of the stack, you can now use a couple of new features of Simple Neurite Tracer to speed up your tracing. These are:
-
-- The menu option "Show MIP overlays at 20% opacity". This overlays the Maximum Intensity Projection over the slice views of your data, regardless of which your current slice is.
-- The key shortcut 'm', while your mouse is over a point in the image, is the same as a left mouse click at the point of maximum intensity under that point throughout the whole stack.
-
-These features are demonstrated in the following screencast. (I'm afraid that the 3D viewer hasn't been captured properly in this screencast, but I hope it's still pretty clear what's going on.)
-
-{% include video platform='youtube' id='pXpMRb1AC4I'%}
diff --git a/_pages/plugins/simple-neurite-tracer/wishlist.md b/_pages/plugins/simple-neurite-tracer/wishlist.md
deleted file mode 100644
index 63f0afe79a..0000000000
--- a/_pages/plugins/simple-neurite-tracer/wishlist.md
+++ /dev/null
@@ -1,53 +0,0 @@
----
-mediawiki: Simple_Neurite_Tracer:_Wishlist
-title: Simple Neurite Tracer › Wishlist
-nav-links: true
-nav-title: Wishlist
----
-
-{% include warning/deprecated new="[SNT](/plugins/snt)"
- old="[Simple Neurite Tracer](/plugins/simple-neurite-tracer)" %}
-
-This is a list of the most commonly requested (or most important) wishlist items for Simple Neurite Tracer.
-
-- Add a page to the wiki about accuracy considerations, particularly for people who are measuring lengths of processes.
-
-
-
-- Path finding and filling are very memory hungry in large stacks. The data structures for storing the progress of these searches should be much more efficient.
-
-
-
-- It would be nice to be able to export paths to NeuroML
-
-
-
-- The "fill volume" option works well, but currently isn't rendered in the 3D viewer and doesn't calculate radii around the path for export. It would be useful to fit spheres within the fill to optimize the midpoint and generate radii.
-
-
-
-- Make the Tubular Geodesics plugins available through the Fiji [Updater](/plugins/updater).
-
-
-
-- There should be an Undo option when tracing - a big job to implement, unfortunately
-
-
-
-- The way that fills are stored in the .traces file format is very inefficient at the moment - it stores enough information to be able to restart the fill from the exact state that the search reached, and this isn't really necessary.
-
-------------------------------------------------------------------------
-
-Done:
-
-- An option to optionally colour the paths by their SWC type
-- An option to set paths to a particular colour
-- An option to export paths as SWC
-- An option to export all neurons as SWC files, i.e. one per connected set of paths
-- You should be able to split paths
-- You should be able to merge branches that meet at a single point. This is important for when people forget to use the join modifier when creating a branch. The suggested course of action is to go back and create a tiny joining path between the original process and the branch. However, to avoid having this additional tiny branch, it would be best to be able to merge them
-- It has been requested that for RGB images, the tracer should continue to convert the image stack to luminance values for tracing internally, but in the interface should instead display the full colour images. I agree, but would like to go further and add an option to display any one of:
- - The original image data.
- - The values which are being traced on, which might be preprocessed or just a simple transformation of the original data
-- The "fit volume" option is very naive, and doesn't work well for noisy stacks. For clear processes it's still a nice way to visualize the traces, but it should be replaced by a better algorithm. Update: this option should be deprecated - for reconstruction it's vastly better to use [the Tubular Geodesics method](/plugins/snt/tubular-geodesics).
-- You should be able to do all the basic tracing operations in the 3D Viewer. e.g. selecting the start point, selecting the subsequent points, and creating joins and branches. This is partially implemented now - you can try switching between the "hand" and "wand" tool and clicking in the 3D viewer. There's no visual feedback yet for what you're doing, however. Ideally it would be nice not to have to switch tool, as well
diff --git a/_pages/plugins/snt/analysis.md b/_pages/plugins/snt/analysis.md
index cd6a0470f4..f18bb3175c 100644
--- a/_pages/plugins/snt/analysis.md
+++ b/_pages/plugins/snt/analysis.md
@@ -8,133 +8,154 @@ forum-tag: snt
update-site: Neuroanatomy
---
-# Sholl Analysis
+# Brain Area Analysis
+See [Graph-based Analysis](#graph-based-analysis).
-There are two [Sholl Analysis](/plugins/sholl-analysis) commands available in SNT's *Analysis* menu. The {% include bc path='Analysis|Shuoll Analysis...'%} option provides a set of pre-defined focal points the user can choose from. Note for the morphology-based focal points (e.g., *Soma*, *Root node(s): Primary apical dendrite(s)*) , the relevant morphology tag(s) must be assigned to the set of paths considered by the analysis. To select a focal point manually, see the following section.
+# Convex Hull Analysis
+_Convex hull_ commands (in SNT main dialog, [Rec. viewer](/plugins/snt/reconstruction-viewer) and [Rec. plotter](/plugins/snt/manual#plotter)) compute the 2D or 3D convex hull of a reconstruction (i.e., the smallest convex polygon/polyhedron that contains the nodes of its paths). Convex hull measurements are defined in [Metrics](/plugins/snt/metrics#convex-hull-boundary-size).
-{% capture text%}
-Sholl Analysis has a dedicated [documentation page](/plugins/sholl-analysis) detailing [parameters](/plugins/sholl-analysis#parameters), [plots](/plugins/sholl-analysis#sholl-plots), and [metrics](/plugins/sholl-analysis#metrics).
-{% endcapture %}
-{% include notice icon="info" content=text %}
+# Measurements
-## Sholl Analysis (by Focal Point)
+SNT provides a couple ways to measure reconstructions. To measure complete cells use {% include bc path='Analysis|Measure...'%} in the main SNT dialog (or {% include bc path='Analyze & Measure'%} in Reconstruction Viewer). A simplified _Quick Measurements_ variant of this command also exists, in which common metrics are immediately retrieved using default settings. To get measurements only on a select group of Paths, first select or filter for the Paths you want to measure in the Path Manager, then use the commands in the Path Manager's {% include bc path='Analyze|Measurements'%} menu.
-
-It is also possible to initiate [Sholl Analysis](/plugins/sholl-analysis) on a tracing in the canvas by manually selecting a focal point. You can do it coarsely by right-clicking near a node and choosing *Sholl Analysis at Nearest Node* from the contextual menu (Shortcut: {% include key keys='Alt|Shift|A' %}.
+{% include img align="center" name="Measurements dialog" src="/media/plugins/snt/snt-measurements-prompt.png" caption="The measurements dialog features an offline guide accessible through the Gear menu." %}
-Alternatively, for precise positioning of the center of analysis:
+The reason for distinguish between branch-based (ie., cell-based) and path-based measurements is flexibility: Path-based measurements can be performed on any structures, even those with loops, while branch-based measurements require the structure to be a [graph-theoretic tree](#graph-based-analysis). The bulk of SNT measurements is described in [Metrics](/plugins/snt/metrics). Measurements available in the GUI are typically single-value metrics. Many others measurements are available via [scripting](/plugins/snt/scripting).
-1. Mouse over the path of interest. Press {% include key key='G' %} to activate it.
-2. Press {% include key keys='Alt|Shift' %} to select a node along the path.
-3. Press {% include key keys='Alt|Shift|A' %} to start analysis.
+Batch measurements of reconstructions can be accomplished via scripting. See, e.g., the [bundled template script](/plugins/snt/scripting#bundled-templates) *Measure\_Multiple\_Files.py*, and related batch scripts for examples.
-
-
-
-
- 
-
- 
- 
-
- 
-
- 
-
-
+For precise positioning of the center of analysis:
-Found at {% include bc path='Utilities|Create Dendrogram'%}, this option generates a {% include wikipedia title="Dendrogram" %} from one connected component (i.e., a single rooted tree structure) in the Path Manager, providing a high-level overview of neurite branching topology. Note that if multiple rooted trees exist in the Path Manager, you will be prompted to choose one of them.
+1. Mouse over the path of interest. Press {% include key key='G' %} to activate it
+ 
+2. Then, select the node to be used as focal point. This can be done in one of two ways:
+ 1. Select a node along the path as you would for forking operation: i.e., by pressing {% include key keys='Alt|Shift' %} while moving the cursor along the path (Note the "Fork Point" label appearing near the cursor on non-display canvases). With {% include key keys='Alt|Shift' %} still pressed, press {% include key keys='A' %} to start the analysis
+ 2. Make the path editable (right-click on the image and choose _Edit Path_ from the contextual menu). Move the cursor along the path until the desired node is highlighted. Press {% include key keys='Alt|Shift|A' %} to start the analysis
-The viewer provides controls for orientation, zoom level, panning, vertex editing and traversal as well as options to display vertex labels and edge weights (which by default are the euclidean distances between adjacent vertices). To see the available key shortcuts, right click on the viewer and choose *Available Shortcuts...*. The plot may be exported in several file formats, including HTML, PNG and SVG.
+NB: The default {% include key keys='Alt|Shift' %} modifier can be simplified in the _Options_ tab of the main dialog.
-Fine-grained programmatic control over SNT's Graph objects is achieved using the [JGraphT API](https://jgrapht.org/javadoc/) in a script. Also relevant is the [sc.fiji.snt.analysis.graph](http://fiji.github.io/SNT/sc/fiji/snt/analysis/graph/package-frame.html) package which provides high-level tools for Graph creation and conversion. See *Graph\_Analysis.py* in the SNT [Script Templates](/plugins/snt/scripting#script-templates) for a basic example.
+The Sholl dialog created by this approach is a variant of the dialog created by running the {% include bc path='Sholl|Sholl Analysis (From Tracings)...'%} from the _Neuroanatomy Shortcuts_ panel, with a couple of changes:
+1. Since the center of analysis is defined precisely on an image, radius step size can be previewed
+2. The *Path filtering* drop-down menu provides additional options to restrict the analysis to the subset of paths selected in the Path Manager
+3. The type of annotations is more specialized and includes:
+ - **Color coded nodes** Intersection counts will be color mapped into path nodes under the _annotation LUT_.
+ - **3D viewer labels image** This generates a synthetic image holding the number of intersections at each distance from the center under _annotation LUT_. This image can then be fed to the "Apply Color Labels" action of the legacy 3D viewer, to "overlay" the mapping on the legacy 3D viewer scene.
-
-
- 
- 
-
-
+# Comparing Reconstructions
+
+SNT can compare up to six groups of cells. The entry point for this type of comparison is twofold:
+- **{% include bc path='Utilities|Compare Reconstructions/Cell Groups...'%}** in the main SNT dialog. This includes a convenience option to compare single reconstruction files.
+- **{% include bc path='Neuronal arbors|Load & Compare Groups...'%}** in Reconstruction Viewer, allowing groups to be tagged, and imported into a common scene while being compared.
-The file selection prompt for this option allows selection of up to four directories containing SWC files. The metric to compare against is chosen from the *Metric* drop-down menu. Optionally, the user may restrict the analysis to specific neurite compartments. After making your selections, press *OK* to run the analysis. The result include multi-panel figure(s) rendering up to ten reconstructions from each group, a window with the metric statistics on each group, a box-plot and a histogram. These figures can all be exported as PNG or SVG.
+The dialog prompt for this feature allows selection of up to six directories containing reconstruction files (SWC, TRACES, JSON, NDF). The metric to compare against is chosen from the *Metric* drop-down menu. Optionally, it is possible to restrict the analysis to specific neurite compartments. After making your selections, press *OK* to run the analysis. The result typically includes:
+- A simple statistical report, including descriptive statistics and a two-sample t-test (when comparing two groups) or one-way ANOVA (when comparing three or more groups)
+- Comparison plots for the chosen metric: Grouped histogram and boxplot
+- _Montages_ of groups. These are multi-panel vignettes of up to 10 group exemplars. These can all be exported as PNG or SVG.
-
- 
-
- 
- 
-
+
SNT is initialized by running {% include bc path='Plugins|NeuroAnatomy|SNT...' %}. All the options in the startup prompt can be set once SNT is opened, but the startup prompt provides the convenience of setting the most important parameters at once.
-- **Image**/**Image File** The image to be traced/analyzed. The drop-down menu will list all images currently open in ImageJ. Alternatively, an image path may be specified by clicking *Browse* and choosing an image file. If no image is chosen, SNT will create an empty display canvas from the computed bounding box of the reconstruction file (if provided).
+- **Image**/**Image file** The image to be traced/analyzed. The drop-down menu will list all images currently open in ImageJ. Alternatively, an image path may be specified by clicking *Browse* and choosing an image file. If no image is chosen, SNT will create an empty display canvas from the computed bounding box of the reconstruction file (if provided).
-- **Reconstruction file** The path of the reconstruction file to be imported. SNT will automatically try to guess if there is a reconstruction file associated with the chosen image by looking at all the reconstruction files (`.traces`, `.(e)swc`, or `.json`) in the image directory, and choosing one that more {% include wikipedia title="Levenshtein distance" %} the image filename.
+- **Reconstruction file** The path of the reconstruction file to be imported. SNT will automatically try fill this field by looking at all the reconstruction files (.traces, .(e)swc, .ndf, or .json) in the image directory and retrieving the filename closer to _Image file_.
- **User interface** Specifies which views to display for 3D images. The default setting provides the XY, ZY, and XZ views and allows for more [accurate node placement](/plugins/snt/step-by-step-instructions#accurate-point-placement) but requires more RAM.
@@ -42,50 +45,87 @@ SNT is initialized by running {% include bc path='Plugins|NeuroAnatomy|SNT...' %
# Main Dialog
+{% include img align="center" src="/media/plugins/snt/snt-main-gui.png" caption="Overview of main dialog (left). Note that clicking on the headings separating the different widgets will point your browser to the relevant section of this manual!" %}
+
## Menu Commands
### File
-
Lists commands for I/O operations. Most are self-explanatory. Noteworthy:
-- {% include bc path='Choose Tracing Image| ' %} Specifies the image to trace on without having to restart SNT. To trace on an image currently open in ImageJ, use *From Open Image...*. A prompt with the currently open images will appear, allowing selection of one. To browse for an image file, use *From File...*. You should toggle the *validate spatial calibration* checkbox to ensure the image to be imported is compatible with the existing one.
+- **{% include bc path='Choose Tracing Image| ' %}** Specifies the image to trace on without having to restart SNT. To trace on an image currently open in ImageJ, use *From Open Image...*. A prompt with currently open images will appear, allowing selection of one. To browse for an image file, use *From File...*. You should toggle the *validate spatial calibration* checkbox to ensure the image to be imported is compatible with the existing one.
-
+- **{% include bc path='Autotrace Segmented Image...| ' %}** If you have a binary mask of the image you want to trace saved to disk (i.e., a pre-processed version of the image in which background pixels have been zeroed), you can use this command to attempt automatic reconstruction. This is similar to {% include bc path='Utilities | Extract Paths from Segmented Image... ' %} but uses file paths as input. See [Full-automated tracing walkthrough](/plugins/snt/step-by-step-instructions#full-automated-tracing) for details.
-- {% include bc path='Import| Labels (AmiraMesh)...' %} This option assumes you are tracing on the same spatial coordinates of an annotated neuropil, for which compartments have been segmented (*labeled*) and stored in an [Amira](https://amira.zib.de/) labels file. Once loaded, SNT will report the name of the compartments in the ImageJ status bar when hovering over the image.
+- **{% include bc path='Load Tracings| ' %}** Imports of neuronal reconstructions from multiple sources, including:
-- {% include bc path='Import| Remote Databases| ' %} Allows import of neuronal reconstructions from the [FlyCircuit](http://www.flycircuit.tw/), [MouseLight](https://ml-neuronbrowser.janelia.org/) and [NeuroMorpho](http://neuromorpho.org/) remote databases.
+ - **{% include bc path='Local Files' %}** [TRACES](/plugins/snt/faq#in-which-format-should-i-save-my-tracings-traces-or-swc), [SWC](/plugins/snt/faq#what-is-a-swc-file) (single files or bulk import of a directory of files), NDF ([NeuronJ](/plugins/neuronj) data format), or JSON.
-- {% include bc path='Export As| SWC| ' %} Allows export of all traced paths in the [SWC](/plugins/snt/faq#what-is-a-swc-file) file format, the most common format for representing neuronal reconstructions. Note that you can also export subsets of paths using the [Path Manager](#path-manager).
+ - **{% include bc path='Remote Databases' %}** Import of neuronal reconstructions from [FlyCircuit](http://www.flycircuit.tw/), [InsectBrain](https://insectbraindb.org/app/), [MouseLight](https://ml-neuronbrowser.janelia.org/), and [NeuroMorpho](http://neuromorpho.org/).
-- {% include bc path='Save Measurements...' %} Allows export of measurements generated by the *Measure...* and *Quick Measurements* commands in the {% include wikipedia title="Comma-separated values" %} file format.
+{% capture dnd %}
+All SNT dialogs (including the _Neuroanatomy Shortcut Window_ support drag-and-drop: E.g., you can import SWC files just by dragging and dropping them either into the main SNT dialog or the Path Manager.
+{% endcapture %}
+{% include notice icon="info" content=dnd %}
-
-
@@ -93,9 +133,15 @@ Lists commands for I/O operations. Most are self-explanatory. Noteworthy:
+If tracing on a multi-dimensional image (i.e., one with multiple data channels and/or a time axis), a particular channel/frame can be loaded into the views by selecting each and pressing the "Reload" button.
+
### Cursor Auto-snapping
**Enable Snapping checkbox** If active (the default) the cursor snaps to the brightest voxel in its vicinity (Toggling shortcut: {% include key key='S' %}). To accomplish this, SNT takes the cuboid of the specified dimensions (in pixels) centered on the current cursor position and searches quickly for local maxima in that neighborhood, moving the cursor to that position. The Z-plane in which the maximum was found is automatically selected if the "Z" parameter is greater than 0. Noteworthy:
-
+
-- This feature assumes the signal is brighter than the background as typically found in fluorescent images.
+ - This feature assumes the signal is brighter than the background as typically found in fluorescent images.
-- If multiple maxima exist (e.g., when the signal is saturated), it snaps to their centroid.
+ - If multiple maxima exist (e.g., when the signal is saturated), it snaps to their centroid.
-- To streamline the computation: XYZ dimensions are constrained to even numbers and limited range.
+ - To streamline the computation: XYZ dimensions are constrained to even numbers and limited range.
-- Snapping occurs in 2D (i.e., in the active plane) if Z=0.
+ - Snapping occurs in 2D (i.e., in the active plane) if Z=0.
-- The XZ, ZY views are synchronized when 3D snapping is active (i.e., Z>0).
+ - The XZ, ZY views are synchronized when 3D snapping is active (i.e., Z>0).
-- This functionallity was inspired by NeuronJ, that described it like this in its manual:
+ - This functionality was inspired by NeuronJ, that described it like this in its manual:
> To facilitate accurate positioning of starting points, so that they are really on a neurite rather than close to one, the program carries out a local snapping operation. This means that when moving the mouse within the image, the program quickly searches in a small window around the current mouse position for the pixel that is most likely to be on a neurite.
### Auto-tracing
-
-- **Enable A\* search algorithm** By default, SNT uses the {% include wikipedia title="A* search algorithm" text="A* search" %} to automatically trace paths between two manually selected points. To manually place nodes in a path, toggle this feature off. Note that it is also possible to enable other algorithms through the installation of SNT add-ons. See [Tubular Geodesics](/plugins/snt/tubular-geodesics) for details.
+
+- **Enable A\* search algorithm** By default, SNT uses the {% include wikipedia title="A* search algorithm" text="A* search algorithm" %} to automatically trace paths between two manually selected points. To manually place nodes along a path, toggle this feature off. Note that it is also possible to enable other built-in algorithms or algorithms provided by external SNT add-ons. Current options include:
-- **Hessian-based analysis** (Toggling shortcut: {% include key key='H' %}) A quick way to improve the quality and efficiency of the pathfinding is to enable this feature, in which paths are computed after filtering the image for tube-like structures. Upon such filtering, SNT will use a measure of [Tubeness](/plugins/tubeness) at each point of the image to define the best path through it, based on eigenvalues and eigenvectors of the {% include wikipedia title="Hessian matrix" %}. The later can be used to infer the likelihood that a point in the image belongs to a tube-like structure. This concept is also known as *vesselness* or *neuriteness*.
+ - **A\* search**: Canonical and proven implementation of the historic algorithm, ported from [Simple Neurite Tracer](/plugins/snt/faq#what-is-the-difference-between-snt-and-simple-neurite-tracer)
-- **Hessian options** (Specified in the *gear* drop-down menu) may be chosen *Manually* (if you already have a quantitative understanding of the image) or *Visually* (generally more intuitive). Hessian analysis requires two parameters to be specified:
+ - **NBA\* search (New Bidirectional A\*)**: [Newer implementation](https://repub.eur.nl/pub/16100/ei2009-10.pdf) of A* expected to be faster than original but not as thoroughly tested
-- **Sigma** Controls the spatial scale of the filter. A lower *sigma* (σ) will capture small scale structure but is more sensitive to noise. A larger σ will consider larger scale structures but is less sensitive to local shape characteristics. It is generally advised to pick a value which reflects the average radius of the structures to be traced. It corresponds to the standard deviation of the 3D Gaussian kernel used to smooth the image prior to *Tubeness* filtering
-- **Maximum** The maximum pixel intensity on the *Tubeness* image beyond which the cost function for A\* search is minimized.
+ - **Fast marching**: Provided by [Tubular Geodesics](/plugins/snt/tubular-geodesics), an external SNT add-on
- If you choose *Visually*, the dialog will prompt you to click on a representative region of the image which has meaningful structure. Once you click there, a 9-square palette is generated showing increasing values of sigma (from top-left to bottom-right) applied to that region of the image. The palette is an image stack which can be scrolled through with the mouse wheel.
+ Independently of the algorithm used, the gear menu in this pane provides options to tweak the performance, accuracy and footprint of the computations involved in the search. These include:
-
+ - **Data structure** Defines how data is stored internally: Either _Map_ (slightly slower, but lower footprint), or _Array_ (slightly faster, but higher footprint)
-
+ - **Difference of Intensity Squared** (Usually) Faster flavor of _Difference of Intensity_
-The {% include bc path='Estimate Radii (Local Thickness)...' %} option in the Hessian gear menu will run the *Local Thickness (complete process)* plugin found in {% include bc path='Analyze|Local Thickness|Local Thickness (complete process)' %} in the main Fiji dialog. This allows automated radii estimation of processes across the image, which can inform the choice of sigma. The user can set the Z-slice range for the analysis to consider, as well as the pixel intensity threshold (pixel values below the threshold are treated as background).
+ - **Probability of Intensity** Fast, specially on noisy images. To be used with 'Real-time statistics' (see below)
-The parameters are:
+ - **Image Statistics** Successful cost functions rely on _a priori_ understanding of the image (simpler cost functions may only require access to the image minimum (dimmest intensity) and maximum (brightest intensity), but many others may need access to the image's mean, standard deviation, etc.). Options include:
-- **First Z-slice** The starting slice of the image to be considered in the estimation.
+ - **Compute Real-Time** The default. Image statistics are computed during _each_ auto-tracing operation, along a bounding-box defined by the start and end points of the search
-- **Last Z-slice** The end slice of the image to be considered in the estimation.
+ - **Specify Manually** Advanced option for users with if a quantitative understanding of the image. Searches may consider pixels outside neurites when maximum in over-estimated, and may take significantly longer when it is under-estimated, since each pixel will carry a greater-than-reasonable cost
-- **Dimmest intensity (approx.)** Pixel values below this value are treated as background when computing the distance map. Use -1 to adopt the default cutoff value (half of the image max).
+ - **Compute Once** Statistics are computed once for the whole image (may take a while for large images) and stored in memory. If enough RAM is available this _may_ speed-up searches. Although in real-word usage any speed-gains relatively to _Compute Real-Time_ seem negligible on modern hardware
-Pressing *OK* will output a color-mapped image (based off local radius) and a histogram showing the distribution of radii across the image. To calibrate the Hessian analysis for smaller processes, one might select a sigma value closer to the minimum estimated thickness, or the opposite for larger processes.
+### Tracing on Secondary Image (Layer)
+
+
+This is one of SNT's most advanced and useful features. The [default auto-tracing](#Auto-tracing) provides a convenient and easy way to detect structures by their likelihood of *belonging* to a tube-like structure (such as a neurite). However, it is just _one_ approach for "tube-like" classification. What if your data requires different filtering?, or you want to experiment with other approaches?, or the perfect pre-processing algorithm for your images is not yet available in SNT? *Tracing on Secondary Layer* is the answer to these questions: It allows you to feed SNT with pre-processed data on which the A\* star search will operate. Because this option can be toggled at will, it becomes a secondary _layer_ for auto-tracing: E.g., you may decide to auto-trace certain neurites on the original image, while tracing other neurites on the secondary layer.
-
- 
-
-- **Show Cached "Tubeness Image"** Displays the *Tubeness* data currently cached. Useful for debugging purposes. Also mirrored in {% include bc path='View | Show Cached/Loaded Hessian (Tubeness) Image' %}.
+Secondary layers are created/load using the second *gear* drop-down menu in the auto-tracing panel. The most common way to create a new layer is by calling the _Secondary Layer Creation Wizard_:
+The wizard needs two types of information from the user: The type of filtering operation and the size(s) (scale(s)) of the structures being traced, which control the spatial scale of the filter (known as σ).
+- **Filter** The filtering operation, including *Frangi*, *Tubeness*, *Gaussian blur* and *Median*. Note rh.
-### Tracing on Secondary Image
+ - **Tubeness** This corresponds to the _Hessian-based analysis_ of older SNT versions. This filter enhances tube-like structures in the image, using an improved [Tubeness](/plugins/tubeness) approach, modified to support multiple scale(s)
-This is one of SNT's most advanced features. [Hessian-based analysis](#Auto-tracing) provides a convenient and easy way to perform auto-tracing on pre-processed data in which voxels defining the traced structure are scored by their likelihood of *belonging* to a tube-like structure. However, it is just one approach for "tubeness" classification. What if your data requires different filtering?, or you want to experiment with other approaches?, or the perfect pre-processing algorithm for your images is not yet available in ImageJ? *Tracing on Secondary Image* is the answer to these questions: It allows you to feed SNT with pre-processed data on which the A\*star search will operate. Here are two specific usages for this option:
+ - **Frangi vesselness** A proven and consistent strategy for filtering tube-like structures. Described in [Frangi](/plugins/frangi)
-- **Frangi *Vesselness* filtering** For certain datasets Frangi filtering ([Frangi et al. 1998](https://link.springer.com/content/pdf/10.1007%252FBFb0056195.pdf)) is more effective than [Tubeness](/plugins/tubeness) at enhancing tube-like structures in the image. However, it is more computation intensive, and thus, less suitable to be adopted by the "compute-as-needed" approach used in Hessian-based analysis. Thus, one can import a pre-computed Frangi-filtered image using this option.
+ - **Median** Filter for noise removal able to preserve neurite edges. Note that _Median_ accepts only one σ value, i.e., a single scale.
-- **Hessian-analysis at multiple scales** Let's consider a structure formed simultaneously by very thick and very thin processes (e.g. axons and dendrites). To trace it one would need to adjust continuously the sigma parameter while tracing. Instead, to trace structures of variable diameters more effectively, one could load a copy of the current image as *secondary image*, and assign different hessian parameters to both images.
+ - **Gaussian blur** Filter for noise removal, capable of gentle smoothing with some ability to preserve neurite edges, specially under small σ values.
-- **Adopting probability maps** Pre-classified images (using e.g., machine learning) could also be loaded here.
-Importantly, this option can be toggled at will, during tracing. Indeed, one can ping-pong between *secondary image* and main image simply, by pressing {% include key key='I' %}, the shortcut for the *Trace on Secondary **I**mage* checkbox.
+- **Scale(s)** Also known as _sigmas_ (σ). These should reflect average radii of the structures being traced. If smaller values are specified, the filter becomes more sensitive to noise. Larger values on the other hand, make the filtering operation less sensitive to local shape characteristics. There are two ways to select this values:
-**Secondary Image options** can be specified in the *gear* drop-down menu, including commands for Loading/displaying the image file and the powerful *Generate Secondary Image* command:
+ - **Select visually...**: The wizard will prompt you to click on a representative region of the image which has a meaningful structure. Once you click there, a preview palette is generated showing increasing values of σ (from top-left to bottom-right) applied to that region of the image. Select the suitable scales
-
-
+ - **Estimate programmatically...**: This allows automated estimation of radii across the image, which can inform the choice of scale(s). The only parameter required is _Dimmest intensity (approx.)_: Pixel values below this value are treated as background when computing thicknesses. Use -1 to adopt the default cutoff value (half of the image max). After pressing *OK*, a color-mapped image (based off local radius) and a histogram showing the distribution of radii across the image are shown. The histogram can be used to validate values chosen _visually_ in the preview palette.
-- **Load Specified File** Loads the filtered image specified in the *File* textbox.
+ NB: Analysis is performed via the *Local Thickness (complete process)* plugin ({% include bc path='Analyze|Local Thickness|Local Thickness (complete process)' %} in Fiji's menu bar).
-- **Generate Secondary Image** Enables processing of the currently open image directly from SNT. Three routines are currently supported: *Frangi*, *Frangi (without Gaussian)* and *Tubeness*. Supports saving and display of the resulting image. To use the currently open image as the secondary image, choose *None. Duplicate Primary Image*. Noteworthy: It is assumed that the current sigma value in the Auto-tracing widget reflects the size of structures to be filtered. If that is not the case, the sigma should be adjusted before running this command.
+NB: The wizard also allows you use a backup copy of the image being traced as secondary layer. This is only useful if you intend to modify the original image during a tracing session, but want to have convenient access to the initial image at a later time.
-- **Adjust Min-Max** Sets the range of pixel intensities used by A\* search.
-- **Show Cached image** Displays the currently loaded filtered image in a separate window.
+
+
+
By default, all the nodes of a path are projected onto the current Z-slice. This is useful to see how much has been completed and gives a sense of the overall structure of the reconstruction. However, SNT provides three additional visibility options for paths:
1. **Only selected paths (hide deselected)** Only show paths that have been manually selected in the Path Manager or with the {% include key key='G' %} key ({% include key keys='Shift|G' %} to select multiple paths).
@@ -251,7 +295,6 @@ Any combination of these options may be toggled simultaneously. Note that these
### Default Path Colors
-
By default, finished paths are colored by their selection status (only selected paths can be edited, or extended). The default colors are Green (selected paths) and Magenta (deselected). Default colors can be customized by pressing the respective button in the widget and using the {% include wikipedia title="CMYK color model" %}. For customizing unconfirmed and temporary paths, see the *Colors* option in the [UI Interaction](#ui-interaction) widget.
@@ -270,22 +313,17 @@ The [Path Manager](#path-manager) offers several ways to colorize Paths:
{% include img src="color-tag-result" width=158 %}
{% include img src="color-tag-result-image" width=221 %}
-
-Note that Path Manager commands are applied to all paths if no paths are selected.
{% endcapture %}
{% include notice icon="info" content=tip %}
+
## Options Tab
This tab aggregated widgets for advanced settings.
-### Data Source
-
-If tracing on a multi-dimensional image (i.e., one with multiple data channels and/or a time axis), a particular channel/frame can be loaded into the views by selecting each and pressing the "Reload" button.
-
### Views
-
+
- **Overlay MIP(s) at X% opacity** Overlays the {% include wikipedia title="Maximum intensity projection" %} of the image "over" the image canvas at the specified opacity. The overlaid projection is only used as a visualization aid and is ignored by the auto-tracing algorithms. It is rendered using the LUT of the channel currently being traced. To reload the overlay (e.g., in case the image being traced changes during a tracing session) toggle the checkbox twice.
+### Temporary Paths
- **Confirm temporary segments** If active, prompts for either confirmation or denial of whether or not to keep an unconfirmed path segment. If inactive, automatically confirms the path segment created on each subsequent node placement after starting a path. Applies to both auto-traced and manually traced path segments. The following two settings are only toggle-able when this setting is active.
- **Pressing 'Y' twice finishes path** Finish a temporary path on two successive {% include key key='Y' %} key presses.
+
- **Pressing 'N' twice cancels path** Discard a temporary or unconfirmed path, including the start node, on two successive {% include key key='N' %} key presses.
-### UI Interaction
-
+### UI Interaction
- **Colors** Specifies how components should be rendered, including:
+
- **Canvas annotations** The label shown on the top-left corner of the views indicating the state of the UI ("Tracing Paused", "Choosing Sigma", etc.)
+
- **Fills** The pixels that have been reached by the Fill search
+
- **Unconfirmed** and **Temporary** paths.
- **Path nodes rendering scale** Adjusts the radius of the drawn circles representing path nodes. A path node is rendered as a circle centered at the XYZ coordinate of the point annotation. The default scale is inferred from the current zoom level.
- **Activate canvas on mouse hovering** If active, moving the mouse cursor over the any of the views automatically brings the view window into focus, allowing it to receive input.
+
### Misc
- **Skip confirmation dialogs** If active, disables the "*Are you sure?*" prompt preceding major actions. Note that this option does not apply to irreversible actions such as deleting paths.
+
- **Debug mode** If active, logs detailed information about actions in the console.
+
- **Preferences...** Allows setting other options, namely:
+
- Whether the position of dialogs should be remembered across restarts
+
- Whether {% include wikipedia title="Gzip" %} compression (lossless) should be used to reduce the storage footprint of ".traces" files.
+
- The max number of parallel threads to be used by SNT, as specified in ImageJ's {% include bc path='Edit|Options|Memory & Threads...' %}
+
- *Reset All Preferences...* Resets all options to their default values. A restart of SNT may be required for changes to take effect.
+
## 3D Tab
-
+
This tab aggregates widgets related to 3D interaction.
### Reconstruction Viewer
-The [Reconstruction Viewer](/plugins/snt/reconstruction-viewer) is an advanced, fully scriptable OpenGL viewer enabling 3D visualization and interaction with reconstructions, OBJ meshes (including multiple model organism neuropil annotations and reference brains), computed surfaces (convex hulls) and other shape annotations. For performance reasons, some Path Manager changes may need to be synchronized manually from the RV controls. To open Reconstruction Viewer with the current contents of the Path Manager, press *Open Reconstruction Viewer*. To instead open the viewer as a standalone application, go to {% include bc path='Plugins|NeuroAnatomy|Reconstruction Viewer...' %} in the main Fiji dialog.
+The [Reconstruction Viewer](/plugins/snt/reconstruction-viewer) is an advanced, fully scriptable OpenGL viewer enabling 3D visualization and interaction with reconstructions, OBJ meshes (including multiple model organism neuropil annotations and reference brains), computed surfaces (convex hulls) and other shape annotations. For performance reasons, some Path Manager changes may need to be synchronized manually from the RV controls. To open Reconstruction Viewer with the current contents of the Path Manager, press *Open Reconstruction Viewer*. To instead open the viewer press _Reconstruction Viewer_ on the [Shortcuts](#startup) dialog.
### sciview
-[sciview](/plugins/sciview) is IJ2's modern replacement for the Legacy 3D Viewer, providing sophisticated 3D visualization and virtual reality capabilities for arbitrarily large image volumes and meshes. Since it is fully integrated with SNT, sciview can enhance tracing, analysis and visualization routines by providing a deeper, more contextualized view of the imagery at hand. Additionally, native integration with [Cx3D](https://github.com/morphonets/cx3d) enables simulation of neurodevelopmental processes, including neuronal growth and formation of cortical circuits. See [SNT: Modeling](/plugins/snt/modeling) for details.
+This option assumes you have [sciview](/plugins/sciview) properly installed. sciview is a modern replacement for the Legacy 3D Viewer, providing sophisticated 3D visualization and virtual reality capabilities for arbitrarily large image volumes and meshes. Integration with [Cx3D](https://github.com/morphonets/cx3d) enables simulation of neurodevelopmental processes, including neuronal growth and formation of cortical circuits. See [SNT: Modeling](/plugins/snt/modeling) for details.
### Legacy 3D Viewer
@@ -358,37 +406,48 @@ The Legacy 3D Viewer is a functional tracing canvas but it depends on outdated s
# Contextual Menu
-
-Right-clicking on any of the image views will bring up a menu with various editing tools. The corresponding keyboard shortcuts are shown to the right of each option.
+{% include img align="left" width="250" name="contextual menu" src="/media/plugins/snt/snt-contextual-menu.png" %}
+
+Right-clicking on any of the tracing views will bring up a menu with various editing tools. The corresponding [keyboard shortcuts](/plugins/snt/key-shortcuts) are shown to the right of each option. The list includes:
+
+**Select Nearest Path** {% include key key='G' %} or {% include key keys='Shift|G' %} Will select the path closest to the mouse cursor.
-- **Select Nearest Path** {% include key key='G' %} or {% include key keys='Shift|G' %} Will select the path closest to the mouse cursor.
+**Fork at Nearest Node** {% include key keys='Shift|Alt|Left Click' %} Creates a fork point at the node closest to the mouse cursor. Once a fork point is made, the branch may be extended as described in [Step-By-Step Instructions](/plugins/snt/step-by-step-instructions#branching-start-a-path-on-an-existing-path).
-- **Fork at Nearest Node** {% include key keys='Shift|Alt|Left Click' %} Creates a fork point at the node closest to the mouse cursor. Once a fork point is made, the branch may be extended as described in [Step-By-Step Instructions](/plugins/snt/step-by-step-instructions#branching-start-a-path-on-an-existing-path).
+**Continue Extending Path** Allows continued tracing of previously finished paths. Note only one path may be extended at a time. To extend a path: first select it, choose this option, then place additional nodes as shown in [Step-By-Step Instructions](/plugins/snt/step-by-step-instructions#ii-pick-a-subsequent-point).
-- **Continue Extending Path** Allows continued tracing of previously finished paths. Note only one path may be extended at a time. To extend a path: first select it, choose this option, then place additional nodes as shown in [Step-By-Step Instructions](/plugins/snt/step-by-step-instructions#ii-pick-a-subsequent-point).
+**Pause SNT** Waives all keyboard and mouse inputs to ImageJ, allowing you to interleave image processing routines with tracing operations. Note that if the image contents change while SNT is paused, the image should be reloaded so that SNT is aware of the changes. Tracing views are annotated with the *SNT Paused* [label](#ui-interaction) to indicate this state.
-- **Pause SNT** Waives all keyboard and mouse inputs to ImageJ, allowing you to interleave image processing routines with tracing operations. Note that if the image contents change while SNT is paused, the image should be reloaded so that SNT is aware of the changes. Tracing views are annotated with the *SNT Paused* [label](/plugins/snt/manual#ui-interaction) to indicate this state.
+**Pause Tracing** Disables tracing functions until this option is deselected. Tracing views are annotated with the *Tracing Paused* [label](/plugins/snt/manual#ui-interaction) to indicate this state.
-- **Pause Tracing** Disables tracing functions until this option is deselected. Tracing views are annotated with the *Tracing Paused* [label](/plugins/snt/manual#ui-interaction) to indicate this state.
+**Sholl Analysis at Nearest Node** {% include key keys='Shift|Alt|A' %} Described in [Analysis › Sholl Analysis (by Focal Point)](/plugins/snt/analysis#sholl-analysis-by-focal-point).
-- **Sholl Analysis at Nearest Node** {% include key keys='Shift|Alt|A' %} Runs the [Sholl Analysis](/plugins/sholl-analysis) plugin found in {% include bc path='Analyze|Sholl|Sholl Analysis (From Tracings)' %}. Note the *Center* parameter, which sets the center point of the analysis, is left out as this value is given by the selected node.
### Editing Paths
-Pressing *Edit Path* with a single path selected will activate *Edit Mode*, allowing use of the menu options under the *Edit Path* option. When *Edit Mode* is active, moving the mouse cursor along the path will activate the nearest node and synchronize the current Z-slice to the location of that node. Note that the ability to create new paths is temporarily disabled when in *Edit Mode*.
+Pressing *Edit Path* with a single path selected will activate *Edit Mode*, allowing use of the menu options under the *Edit Path* option. When *Edit Mode* is active, moving the mouse cursor along the path will activate the nearest node and synchronize the current Z-slice to the location of that node. Note that the ability to create new paths is temporarily disabled when in *Edit Mode*. The list of editing commands includes:
+
+- **Reset Active Node** Clears the active node under the cursor.
+
+- **Delete Active Node** {% include key key='D' %} Permanently removes the active node from the path.
-- **Reset Active Node** Clears the active node from the cursor.
-- **Delete Active Node** {% include key key='D' %} or {% include key key='Backspace' %} Permanently removes the active node from the path.
- **Insert New Node At Cursor Position** {% include key key='I' %} Inserts a new node at the cursor position. The inserted node is placed between the active node and its parent.
+
- **Move Active Node to Cursor Position** {% include key key='M' %} Moves the active node to the cursor position.
+
- **Bring Active Node to Current Z-plane** {% include key key='B' %} Moves the active node to the active Z-plane. Note that the translation is only done in Z. XY positions are unchanged.
-- **Connect To (Start Join)** Allows two existing paths to be [merged or joined](/plugins/snt/step-by-step_instructions#mergingjoining-paths).
+
+- **Connect To (Start Join)** Allows two existing paths to be [merged or joined](/plugins/snt/step-by-step-instructions#mergingjoining-paths).
+
# Path Manager
- The Path Manager dialog displays all existing paths in a hierarchical structure (tree), where one path is "primary" (path 0) and all other paths (paths 1...N) are children of the primary path. The dialog also contains several menus with various editing, tagging, refinement/fitting, filling and analysis options. Paths can be searched by name and/or tags in the text filter, with more sophisticated search capabilities in the Advanced Filtering Menu.
+ The Path Manager dialog displays all existing paths in a hierarchical structure (tree), where one path is "primary" or "root" (path 0) and all other paths (paths 1...N) are children of the primary path. This pattern repeats for each cell being traced. The dialog also contains several menus with various editing, tagging, refinement/fitting, filling and analysis options. Paths can be searched by name and/or tags in the text filter, with more sophisticated search capabilities in the Advanced Filtering Menu.
+
+{% include notice icon="info" content="Path Manager commands are applied to all paths if no paths are selected." %}
+
## Menu Commands
@@ -396,18 +455,33 @@ Pressing *Edit Path* with a single path selected will activate *Edit Mode*, allo
-- {% include bc path='Delete...' %} Removes selected Path(s) from the Path Manager. If no Paths are selected, all Paths are deleted.
-- {% include bc path='Rename...' %} Renames the selected Path. Only one Path may be renamed at a time.
-- {% include bc path='Make Primary' %} Makes the selected Path the primary Path, moving it to the top of the tree hierarchy. Note that this will alter parent-child relationships between Paths and, by consequence, individual nodes.
-- {% include bc path='Disconnect...' %} Disconnects the selected Path from all of its connected Path(s) (Undoable operation).
-- {% include bc path='Merge...' %} Merges the selected Paths (at least two) into one. Note the starting node of Path *i* is merged to the endpoint of Path *i+1*.
-- {% include bc path='Specify Radius...' %} Assigns a constant radius to all the nodes of selected Path(s). This setting only applies to unfitted Paths and overrides any existing values.
-- {% include bc path='Ramer-Douglas-Peuker Downsampling...' %} Given an inputted maximum permitted distance between adjacent nodes, performs {% include wikipedia title="Ramer–Douglas–Peucker algorithm" %} downsampling on the selected Path(s).
+- **{% include bc path='Delete...' %}** Removes selected Path(s) from the Path Manager. If no Paths are selected, all Paths are deleted.
+
+- **{% include bc path='Duplicate...' %}** Duplicates the selected path. Only one Path my be duplicated at a time
+
+- **{% include bc path='Rename...' %}** Renames the selected Path. Only one Path may be renamed at a time. Path names are expected to be unique.
+
+- **{% include bc path='Merge Primary Path(s) into Shared Root' %}** Takes two or more primary paths and merges them into a common root node placed at the centroid defined by starting nodes of the primary paths to be merged. This is useful, e.g., when all the paths around a soma have been traced without passing through it. Note that this will alter parent-child relationships between Paths and, by consequence, individual nodes.
+
+- **{% include bc path='Combine...' %}** Combines two or more _disconnected_ paths into one (undoable operation)
+
+- **{% include bc path='Concatenate...' %}** Concatenates two or more paths into a single un-branched segment.
+
+- **{% include bc path='Disconnect...' %}** Disconnects the selected Path from all of its connected Path(s) (Undoable operation).
+
+- **{% include bc path='Specify Radius...' %}** Assigns a constant radius to all the nodes of selected Path(s). This setting only applies to unfitted Paths and overrides any existing values.
+
+- **{% include bc path='Specify No. Spine\Varicosity Markers...' %}** Assigns the no. of markers (e.g., spines or varicosities) to be associated to selected path(s)
+
+- **{% include bc path='Ramer-Douglas-Peuker Downsampling...' %}** Given an inputted maximum permitted distance between adjacent nodes, performs {% include wikipedia title="Ramer–Douglas–Peucker algorithm" %} downsampling on the selected Path(s).
+
+- **{% include bc path='Rebuild...' %}** Resets all Path IDs and recompute connectivity for all paths. Useful to reset ill-relationships created from mis-editing paths.
+
### Tag
-Assigns tags to Paths. Tags are organized in the following categories:
+Assigns tags to Paths. Tags allow for paths to be searched, selected, and bookmarked. Tags are organized in the following categories:
- {% include bc path='Type| ' %} Type of neurite compartment (*Axon*, *(Basal) Dendrite*, *Soma*, etc.), as used by the SWC file format. It is also possible to pair each type with a color tag through the {% include bc path='Tag|Options..' %} dialog
These tags are considered to be essential annotations and all paths are assigned the *Undefined*-type tag when created. For this reason they are not eliminated by the *Remove All Tags* command.
@@ -418,19 +492,24 @@ Assigns tags to Paths. Tags are organized in the following categories:
- {% include bc path='Morphometry| ' %} Morphometric properties, such as *Path length*, *Path mean radius* or *[Path order](/plugins/snt/analysis#path-order-analysis)*.
-- {% include bc path='Custom...' %} Ad-hoc comments.sss
+- {% include bc path='Custom...' %} Ad-hoc comments.
Note that only SWC-type tags are preserved across restarts when saving traces in the SWC format. All others require data to be saved in SNT's own .Traces format.
### Refine/Fit
+{% capture text%}
+Fitted radii are only exported to [SWC files](/plugins/snt/faq#in-which-format-should-i-save-my-tracings-traces-or-swc) when _Replace existing nodes_ is chosen in {% include bc path='Refine|Parameters...' %}.
+{% endcapture %}
+{% include notice icon="info" content=text %}
+
SNT can use the fluorescent signal around traced Paths to optimize curvatures and estimate the thickness of traced structures to sub-voxel accuracy. The optimization algorithm uses pixel intensities to fit circular cross-sections around each node. Once computed, fitted cross-sections can be used to: 1) Infer the radius of nodes, and/or 2) refine node positioning, by snapping their coordinates to the cross-section centroid. The {% include bc path='Refine/Fit|' %} menu contains three entries:
- {% include bc path='Fit Path(s).../Un-fit Path(s)/Apply Existing Fit' %} This option will change depending on which Path(s) are currently selected. You can use it to 1) Fit selected Path(s), 2) un-fit Path(s) that have already been fitted, or 3) apply a generated preview of the fit or an existing fit.
-- {% include bc path='Explore/Preview Fit' %} Carves out a region of the image along and around each Path node, generating an animated cross-view "fly-through" with the result of the fitting operation. The generated image is annotated with details of the fit: i) Fitted radius; ii) normalized score quantifying the "circularity" of a node's cross section, and iii) the angle between node and parent tangent vectors.
+- {% include bc path='Explore/Preview Fit' %} Carves out a region of the image along and around each Path node, generating an animated cross-view "fly-through" with the result of the fitting operation. The generated image is annotated with details of the fit: i) Fitted radius; ii) normalized score quantifying the "circularity" of a node's cross-section, and iii) the angle between node and parent tangent vectors.
- {% include bc path='Discard Fit(s)...' %} Deletes the existing fit(s) for the selected Path(s), or all fits if no Paths are selected.
Before computing the fit, SNT will prompt you to specify two parameters:
@@ -455,14 +534,20 @@ Assuming you chose to fit both centroids and radii, a fitted path might look lik
### Analyze
-This menu contains several options which provide quick ways to analyze and visualize numerical properties of paths. Note that these operations are only applied to the subset of currently selected Path(s). To apply these operations to the entire Tree, deselect all Paths first.
+This menu contains several options which provide quick ways to analyze and visualize numerical properties of paths and associated branches. Note that these operations are only applied to the subset of currently selected Path(s). To apply these operations to the entire Tree, deselect all Paths first.
+
-- {% include bc path='Color Coding...' %} Assigns color codes to paths based on the chosen metric.
+- **{% include bc path='Color Coding...' %}** Assigns color codes to paths or cells based on the chosen metric.
+
- *Color by* Drop-down menu containing the metrics which inform the color mapping.
+
- *LUT* Drop-down menu containing the LUTs (Look Up Tables) that define the color palettes. The LUTs are those that come packaged with ImageJ. The selected LUT is displayed in the color bar directly underneath.
+
- *Rec. Viewer Color Map* If active, opens an instance of the Reconstruction Viewer with the selected paths color coded with the selected LUT.
+
- *Rec. Plotter Color Map* If active, open an instance of the Reconstruction Plotter with the selected paths color coded with the selected LUT.
+
- *Remove Existing Color Coding* Removes existing color coding from the selected paths.
- 
- 
- 
- *Roi filtering*: If an area ROI exists over the image (you may need to pause SNT to create such an ROI), then only paths inside it will be converted.
+
- *Run "Analyze Skeleton" after conversion* Runs the [AnalyzeSkeleton](/plugins/analyze-skeleton) plugin on the skeletonized output image.
-- {% include bc path='Save Subset as SWC...' %} Exports the selected subset of Path(s) as an [SWC](http://www.neuronland.org/NLMorphologyConverter/MorphologyFormats/SWC/Spec.html) file. Note the paths to be exported must include a primary path (i.e., one at the top level in the Path Manager hierarchy).
+- **{% include bc path='Straighten' %}** Creates a 'linear image' from the pixels associated with a single paths, similarly to [/plugins/straighten](ImageJ's Straighten) command
+
+- **{% include bc path='Train Weka Classifier' %}** Uses selected Path(s) to train a random forest classifier (a machine learning algorithm for semantic segmentation) aimed at classifying neurite-associated pixels. Classification is performed by [/plugins//tws](Trainable Weka Segmentation). The resulting classification can be exported into other software, or loaded as secondary tracing layer. Refer to the prompt's built-in documentation for more details.
+
+- **{% include bc path='Spine/Varicosity Utilities| ' %}** This menu contains commands tools for analyzing at manually placed markers along paths such as dendritic spines or axonal varicosities. The starting point for such analyses are multipoint ROIs placed along paths. These are detailed in [Step-by-step instructions](/plugins/snt/step-by-step-instructions#spinevaricosity-analysis).
+
+- **{% include bc path='Time-lapse Utilities| ' %}** This menu contains commands tools for analyzing time-lapse videos, and assume that the same structure has been traced across multiple frames. Refer to [Step-by-step instructions](/plugins/snt/step-by-step-instructions#time-lapse-analysis) for more details.
+
+- **{% include bc path='Save Subset as SWC...' %}** Exports the selected subset of Path(s) as an [SWC](http://www.neuronland.org/NLMorphologyConverter/MorphologyFormats/SWC/Spec.html) file. Note the paths to be exported must include a primary path (i.e., one at the top level in the Path Manager hierarchy).
## Filter Toolbar
@@ -518,13 +611,20 @@ The filter toolbar allows paths to be searched and filtered quickly using tags (
- **Color Filters**  Allows filtering of Paths by color tags. Custom colors may be selected by right-clicking an empty swatch, which will bring up the CMYK palette. The chosen color is temporarily saved in that swatch.
+
- **Morphology Filters**  Allows filtering of Paths by selected morphological properties (including cell identity). Note that these filters do not require Paths to be labeled using {% include bc path='Tag|Morphology| ' %}.
- - *Path Order...* Filters for Paths of [Path order](/plugins/snt/analysis#path-order-analysis) in the inputted range. Example queries: `1-2`: selects all primary and secondary branches; `max-max`: selects all terminal branches.
+
+ - *Path Order...* Filters for Paths of [Path order](/plugins/snt/analysis#path-order-analysis) in the inputted range. Example queries: `1-2`: selects all primary and secondary paths; `max-max`: selects all terminal paths.
+
- *Length...* Filters for Paths of length within the inputted range. Example queries: `10-20`: selects all Paths with lengths between 10 and 20μm; `max-max`: selects the longest path(s).
+
- *Mean Radius...* Filters for Paths of mean radius within the inputted range.
+
- *No. of Nodes...* Filters for Paths with node count within the inputted range.
+
- *SWC Type...* Filters for Paths with the selected SWC type tags. Note that the Paths of interest must have been [tagged](/plugins/snt/manual#tag) using the{% include bc path='Tag|Type|' %} menu.
+
# Fill Manager
Provides controls for all filling operations. It is described in more detail in the [Filling: Step-By-Step Instructions](/plugins/snt/step-by-step-instructions#filling).
diff --git a/_pages/plugins/snt/metrics.md b/_pages/plugins/snt/metrics.md
new file mode 100644
index 0000000000..15c6c6d425
--- /dev/null
+++ b/_pages/plugins/snt/metrics.md
@@ -0,0 +1,274 @@
+---
+title: SNT › Metrics
+nav-links: true
+nav-title: Metrics
+artifact: org.morphonets:SNT
+icon: /media/icons/snt.png
+forum-tag: snt
+update-site: Neuroanatomy
+---
+
+## Metrics
+{% capture text%}
+This list reflects only the default measurements available in the GUI and is not exhaustive. Note that some of the metrics described here have been ported from [L-measure](http://cng.gmu.edu:8080/Lm/help/index.htm): {% include citation doi='10.1038/nprot.2008.51' %}
+{% endcapture %}
+{% include notice icon="info" content=text %}
+
+
+###### Branch contraction
+
+The ratio between the Euclidean distance of a branch (i.e., Euclidean distance between the first and last node of the branch) and its path length Range of values: ]0--1[ (unitless)
+
+###### Branch fractal dimension
+[L-measure metric](http://cng.gmu.edu:8080/Lm/help/index.htm). The slope obtained from the log-log plot of Path distance vs Euclidean distance. Is only computed for branches defined by at least five nodes. Described in: {% include citation doi='10.1002/cne.21418' %}
+
+###### Branch length
+The path length of a branch (i.e., the sum of all its inter-node distances)
+
+###### Branch mean radius
+The average of the radii of the nodes defining a branch
+
+###### Branch surface area
+_Estimated_ surface area of a branch computed from treating each inter-node segment as a conical frustum and summing the surface area of all frusta
+
+###### Branch volume
+_Estimated_ volume of a branch computed from treating each inter-node segment as a conical frustum and summing the volume of all frusta
+
+
+###### Cable length
+The total path length of a structure, i.e., the sum of all inter-node distances of its paths
+
+###### Complexity index
+Also known as "Dendritic Complexity Index". An index based on the number of primary neurites, total arbor length, and the number and Strahler-order of terminal branches. Described in: {% include citation doi='10.1523/JNEUROSCI.19-22-09928.1999' %}
+
+###### Convex hull: Boundary size
+The perimeter of the 2D polygon or the surface area of the 3D polyhedron of the convex hull
+
+###### Convex hull: Boxivity
+The extent to which the convex hull approaches a rectangle (2D) or a cuboid (3D). Range of values: 0--1 (unitless)
+
+###### Convex hull: Centroid-root distance
+The distance between the root of a neuronal arbor and the centroid of its convex hull
+
+###### Convex hull: Elongation
+The caliper diameter of the convex hull
+
+###### Convex hull: Roundness
+The extent to which the convex hull approaches a circle (2D) or a sphere (3D). Range of values: 0--1 (unitless)
+
+###### Convex hull: Size
+Either the area of the 2D polygon, or the volume of the 3D polyhedron defining the convex hull
+
+
+###### Depth
+The depth of the bounding box embedding the structure being measured
+
+
+###### Height
+The height of the bounding box embedding the structure being measured
+
+###### Horton-Strahler bifurcation ratio
+The average bifurcation ratio of [Strahler bifurcation ratios](https://en.wikipedia.org/wiki/Strahler_number#Bifurcation_ratio)
+
+###### Horton-Strahler number
+The highest Horton-Strahler number of a tree, i.e., the Horton-Strahler number of its root node
+
+
+###### Internode distance
+The distance between nodes defining a branch or a Path
+
+###### Internode distance (squared)
+The squared distance between nodes defining a branch or a Path. Alternative to _Internode distance_ when faster computations are required.
+
+
+###### Length of inner branches
+The sum of branch lengths of branches of highest Strahler order. Typically, these correspond to the most 'internal' branches of an arbor, in direct sequence from the root. Note that_Primary branches_ are _inner branches_ starting at the tree's root.
+
+###### Length of longest shortest path
+Considering a [graph-theory tree](https://en.wikipedia.org/wiki/Tree_(graph_theory)), the _Length of longest shortest path_ corresponds to the [graph diameter](https://mathworld.wolfram.com/GraphDiameter.html). Note that this metric can only be computed for structures that are valid mathematical trees.
+
+###### Length of primary branches
+The sum of branch lengths of primary (or root-associated) branches. Primary branches have origin in a tree's root, extending to the closest branch point or end-point, i.e., they are _inner branches_ starting at the root. Note that a primary branch can also be terminal.
+
+###### Length of terminal branches
+The sum of branch lengths of branches ending at terminal endpoints (tips)
+
+
+###### No. of branch nodes (branch fragmentation)
+ The total number of nodes (and thus _compartments_) in a branch
+
+###### No. of branch points
+The total number (count) of branch points (also know as fork points)
+
+###### No. of branches
+The total number (count) of branches
+
+###### No. of fitted paths
+The total number (count) of [fitted](/plugins/snt/manual#refinefit) paths
+
+###### No. of inner branches
+The number of branches of highest Strahler order. Typically, these correspond to the most 'internal' branches of an arbor, in direct sequence from the root
+
+###### No. of path nodes (path fragmentation)
+ The total number of nodes (and thus _compartments_) in a path
+
+###### No. of paths
+The total number (count) of paths defining a structure
+
+###### No. of primary branches
+The total number (count) of primary (or root-associated) branches. Primary branches have origin in a tree's root, extending to the closest branch point or end-point, i.e., they are _inner branches_ starting at the root. Note that a primary branch can also be terminal.
+
+###### No. of spines/varicosities
+Sum of all spine/varicosity markers in a structure
+
+###### No. of spines/varicosities per path
+Number of spines/varicosities associated with a path
+
+###### No. of terminal branches
+The total number (count) of branches ending at terminal endpoints (tips)
+
+###### No. of tips
+The total number (count) of terminal endpoints in a structure
+
+###### No. of total nodes
+The total number (count) of nodes in a structure
+
+###### Node intensity values
+The pixel intensity at each node location
+
+###### Node radius
+The radius at each node, typically obtained from [fitting procedures](/plugins/snt/manual#refinefit)
+
+
+###### Partition asymmetry
+[L-measure metric](http://cng.gmu.edu:8080/Lm/help/index.htm). Computed at each bifurcation point of the structure being measured. Note that branch points with more than 2 children are ignored. Given _n1_, _n2_ the number of tips on each side of a bifurcation point, Partition asymmetry is defined as _abs(n1-n2)/(n1+n2-2)_.
+
+###### Path channel
+The color channel associated with a path (multi-dimensional image)
+
+###### Path contraction
+The ratio between the Euclidean distance of a path (i.e., Euclidean distance between the first and last node of the path) and its path length. Range of values: ]0--1[ (unitless)
+
+###### Path frame
+The time-lapse frane associated with a path (multi-dimensional image)
+
+###### Path length
+The sum of all inter-node distances in a path
+
+###### Path mean radius
+The average of the radii of the nodes defining a path
+
+###### Path order
+See [Path Order Analysis](/plugins/snt/analysis#path-order-analysis)
+
+###### Path spine/varicosity density
+The number (count) of spine/varicosity markers associated with a path, divided by its path length
+
+###### Path surface area
+_Estimated_ surface area of a path computed from treating each inter-node segment as a conical frustum and summing the surface area of all frusta
+
+###### Path volume
+_Estimated_ volume of a path computed from treating each inter-node segment as a conical frustum and summing the volume of all frusta
+
+
+###### Remote bif. angles
+The angle between each bifurcation point and its children in the simplified graph, which comprise either branch points or terminal nodes. Note that branch points with more than 2 children are ignored.
+
+
+###### Sholl: Decay
+The [Sholl regression coefficient](/plugins/sholl-analysis#sholl-decay)
+
+###### Sholl: Degree of Polynomial fit
+The polynomial degree used to fit the Sholl profile. See [Sholl › Fitting functions](/plugins/sholl-analysis#eq1)
+
+###### Sholl: Kurtosis
+See [Kurtosis](/plugins/sholl-analysis#kurtosis) in [Sholl › Metrics based on sampled data](/plugins/sholl-analysis#metrics-based-on-sampled-data)
+
+###### Sholl: Max
+See [Max inters.](/plugins/sholl-analysis#max-inters) in [Sholl › Metrics based on sampled data](/plugins/sholl-analysis#metrics-based-on-sampled-data)
+
+###### Sholl: Max (fitted)
+See [Critical value](/plugins/sholl-analysis#critical-value) in [Sholl › Metrics based on fitted data](/plugins/sholl-analysis#metrics-based-on-fitted-data)
+
+###### Sholl: Max (fitted) radius
+See [Critical radius](/plugins/sholl-analysis#critical-radius) in [Sholl › Metrics based on fitted data](/plugins/sholl-analysis#metrics-based-on-fitted-data)
+
+###### Sholl: Mean
+See [Mean inters.](/plugins/sholl-analysis#mean-inters) in [Sholl › Metrics based on sampled data](/plugins/sholl-analysis#metrics-based-on-sampled-data)
+
+###### Sholl: No. maxima
+The number of times _Max inters._ occurs in a Sholl profile. See [Max inters.](/plugins/sholl-analysis#max-inters) in [Sholl › Metrics based on sampled data](/plugins/sholl-analysis#metrics-based-on-sampled-data)
+
+###### Sholl: No. secondary maxima
+The number of times a secondary peak occurs in a Sholl profile. See [Max inters.](/plugins/sholl-analysis#max-inters) in [Sholl › Metrics based on sampled data](/plugins/sholl-analysis#metrics-based-on-sampled-data)
+
+###### Sholl: Ramification index
+See [Schoenen Ramification index](/plugins/sholl-analysis#schoenen-sampled) in [Sholl › Metrics based on sampled data](/plugins/sholl-analysis#metrics-based-on-sampled-data)
+
+###### Sholl: Skeweness
+See [Skeweness](/plugins/sholl-analysis#skeweness) in [Sholl › Metrics based on sampled data](/plugins/sholl-analysis#metrics-based-on-sampled-data)
+
+###### Sholl: Sum
+See [Sum inters.](/plugins/sholl-analysis#sum) in [Sholl › Metrics based on sampled data](/plugins/sholl-analysis#metrics-based-on-sampled-data)
+
+###### Surface area
+Treating each inter-node segment as a conical frustum, the sum of the surface areas of all frusta
+
+
+###### Volume
+Treating each inter-node segment as a conical frustum, the sum of the volume of all frusta
+
+###### Width
+The width of the bounding box embedding the structure being measured
+
+###### X,Y,Z coordinates
+Cartesian coordinates in the three-dimensional space
+
+
+## Statistics
+SNT assembles comparison reports and simple statistical reports (two-sample t-test/one-way ANOVA) for up to six groups of cells. This is described in [Comparing Reconstructions](/plugins/snt/analysis#comparing-reconstructions).
+
+
+## Glossary
+
+###### Mesh
+A polygon mesh defines the shape of a three-dimensional polyhedral object. In neuronal anatomy, meshes define neuropil annotations, typically compartments of a reference brain atlas (e.g., the hippocampal formation in mammals, or mushroom bodies in insects)
+
+###### Multi-dimensional image
+An image with more than 3 dimensions (3D). Examples include fluorescent images associated with multiple fluorophores (multi-channel) and images with a time-dimension (time-lapse videos). A 3D multi-channel timelapse has 5 dimensions
+
+###### Neurite
+Same as neuronal process. Either an axon or a dendrite
+
+###### Path
+Can be defined as a sequence of branches, starting from soma or a branch point until a termination. In manual and assisted (semi-automated) tracing, neuronal arbors are traced using paths, not branches. Fitting algorithms that take into account voxel intensities can be used to refine the center-line coordinates of a path, typically to obtain more accurate curvatures. Fitting procedures can also be used to estimate the volume of the neurite(s) associated with a path
+
+###### (Neuronal) morphometry
+Quantification of neuronal morphology
+
+###### Neuropil
+Any area in the nervous system. The cellular tissue around neuronal processes
+
+###### Out-of-core
+Software with out-of-core capabilities is able to process data that is too large to fit into a computer’s main memory
+
+###### Reconstruction
+See Tracing
+
+###### ROI
+Region of Interest. Define specific parts of an image to be processed in image processing routines
+
+###### Skeleton
+A thinned version of a digitize shape (such as a neuronal reconstruction) or of a binary image
+
+###### Tracing
+A digital reconstruction of a neuron or neurite. The term predates computational neuroscience and reflects the manual ‘tracing’ on paper performed with camera lucida devices by early neuroanatomists
+
+###### Volume rendering
+A visualization technique for displaying image volumes (3D images) directly as 3D objects
+
+
+{% capture text%}
+This glossary was assembled from the supplementary note of SNT's publication: {% include citation id='plugins/snt' %}
+{% endcapture %}
+{% include notice icon="info" content=text %}
\ No newline at end of file
diff --git a/_pages/plugins/snt/reconstruction-viewer.md b/_pages/plugins/snt/reconstruction-viewer.md
index 736db24dfb..b5e58b27cc 100644
--- a/_pages/plugins/snt/reconstruction-viewer.md
+++ b/_pages/plugins/snt/reconstruction-viewer.md
@@ -1,7 +1,7 @@
---
title: SNT › Reconstruction Viewer
nav-links: true
-nav-title: Reconstruction Viewer
+nav-title: Rec. Viewer
artifact: org.morphonets:SNT
icon: /media/icons/snt.png
forum-tag: snt
@@ -11,7 +11,7 @@ forum-tag: snt
SNT's Reconstruction Viewer is a powerful OpenGL 3D visualization tool for both surface meshes and reconstructions. It can be used as a standalone program or from withing SNT. Some of its features include:
- Interactive scenes (controlled rotations, panning, zoom, scaling, animation, "dark"/"light" mode)
- - Suport for axes, transparency, color interpolation and path smoothing
+ - Support for axes, transparency, color interpolation and path smoothing
- Tools for management and customization of scene elements
- Ability to render both local and remote files on the same scene
- Loading of surface meshes of several template brains (Drosophila, zebrafish, and mouse (Allen Mouse Brain Atlas))
diff --git a/_pages/plugins/snt/scripting.md b/_pages/plugins/snt/scripting.md
index c2ed7087b4..f147edc767 100644
--- a/_pages/plugins/snt/scripting.md
+++ b/_pages/plugins/snt/scripting.md
@@ -9,7 +9,7 @@ update-site: Neuroanatomy
---
{% capture api%}
-The most up-to-date SNT API can be found at [https://morphonets.github.io/SNT](https://morphonets.github.io/SNT).
+The most up-to-date SNT API can be found at [https://javadoc.scijava.org/SNT](https://javadoc.scijava.org/SNT).
{% endcapture %}
{% include notice icon="info" content=api %}
@@ -17,78 +17,49 @@ The most up-to-date SNT API can be found at [https://morphonets.github.io/SNT](h
A key feature of SNT is its extensibility via scripts.This section provides an overview to the ever-growing list of SNT scripts. These can be accessed through the {% include bc path='Plugins|NeuroAnatomy|Neuroanatomy Shortcut Window' %}, the *Scripts* menu in the main dialog, or the {% include bc path='Templates|Neuroanatomy'%} menu of Fiji's Script Editor. Typically, holding {% include key key='Shift' %} while selecting a script from a menu outside the [Script Editor](/scripting/script-editor) will open it.
-SNT Scripts are intentionally written in multiple languages, but the majority is written in [Groovy](/scripting/groovy/)and [Python](/scripting/python) (Jython), for no other reason that those seem to be the most commonly used language by its developers
+SNT Scripts are intentionally written in multiple languages to demonstrate flexibility, but the majority is written in [Groovy](/scripting/groovy/) and [Python](/scripting/python) (Jython), for no other reason that those seem to be the most commonly used language by its developers. [script parameters](/scripting/parameters) are typically used for rapid development.
+
+## Bundled Templates
+{% include img align="right" src="/media/plugins/snt/snt-scripts-menu.png" width="200px" caption="Scripts menu in main dialog"%}
+There are ~50 scripts currently bundled in SNT. These are organized into non-rigid categories: *Analysis* (typically handling quantifications) , *Batch* (Bulk processing of files), *Render* (visualization), *Skeletons & ROIs* (pixel-based analyses), *Tracing* (Tracing-related tasks), and *Demos*.
+
+Your script can also be bundled with SNT, or made available through the Neuroanatomy update site. Did you write a useful routine? Please [announce it](https://forum.image.sc/tag/snt), or submit a [pull request](https://github.com/morphonets/SNT/pulls) so that it can be distributed with Fiji!
## Adding Scripts to SNT
There are a couple of ways to have your own scripts appear in SNT's *Scripts* menu:
-Any script saved into Fiji's "scripts" sub-directory containing *SNT* in the filename (e.g., `C:\Users\user\Desktop\Fiji.app\scripts\My_SNT_Script.py` or `/home/user/Fiji.app/scripts/My_SNT_Script.py`) will be listed in {% include bc path='Scripts'%} menu:
+Any script saved into Fiji's "scripts" sub-directory containing *SNT* in the filename (e.g., *C:\Users\user\Desktop\Fiji.app\scripts\My_SNT_Script.py* or */home/user/Fiji.app/scripts/My_SNT_Script.py*) will be listed in {% include bc path='Scripts'%} menu:
-1. Go to {% include bc path='Scripts|New...'%} from the SNT dialog. This will open an instance of Fiji's Script Editor with pre-loaded boilerplate code in the scripting language of your choice.
+1. Go to {% include bc path='Scripts|New...'%} from the SNT dialog. You can choose to open an instance of Fiji's Script Editor with pre-loaded boilerplate code in the scripting language of your choice or to assemble your boilerplate using the [Script Recorder](#script-recorder)
-2. Save the script in `Fiji.app/scripts/` including 'SNT' anywhere in its file name
+2. Save the script in *Fiji.app/scripts/* including 'SNT' anywhere in its file name
3. Run {% include bc path='Scripts|Reload...'%}, and your new script should appear in the full list of scripts found at {% include bc path='Scripts|Full List...'%}.
-Did you write a useful script? Please submit a [pull request](https://github.com/morphonets/SNT/pulls) on GitHub so that it can be distributed with Fiji!
-
-## Script Interpreter
-
-Some of SNT's functionality is accessible in the [Script Interpreter](/scripting/interpreter). Here is an example:
-
-
-
-These typically demonstrate various aspects of analysis, tracing, image processing and batch processing routines.
-
-### Analysis
-
-- **Analysis\_Demo\_(Interactive).py** Exemplifies how to programmatically interact with a running instance of SNT to analyze traced data. Because of all the GUI updates, this approach is *significantly slower* than analyzing reconstructions directly (see Analysis\_Demo.py for comparison)
-
-- **Analysis\_Demo.py** A [Jython](/scripting/jython) demo of how SNT can analyze neuronal reconstructions fetched from online databases such as MouseLight, NeuroMorpho or FlyCircuit.
-
-- **Download\_ML\_Data.groovy** Exemplifies how to programmatically retrieve data from MouseLight's database at \[//ml-neuronbrowser.janelia.org ml-neuronbrowser.janelia.org\]: It iterates through all the neurons in the server and downloads data (both JSON and SWC formats) for cells with soma associated with the specified Allen Reference Atlas (ARA) compartment. Downloaded files will contain all metadata associated with the cell (i.e., labeling used, strain, etc.)
-
-- **Get\_Branch\_Points\_in\_Brain\_Compartment.groovy** Exemplifies how to extract morphometric properties of a MouseLight cell associated with a specific brain region/neuropil compartment. Requires internet connection.
+## Script Recorder
-- **Graph\_Analysis.py** Demonstrates how to handle neurons as graph structures {% include wikipedia title="Graph theory" %} in which nodes connected by edges define the morphology of the neuron. SNT represents neurons as directed graphs (assuming the root -typically the soma- as origin) and allows data be processed using the powerful [jgrapht](https://jgrapht.org/) library. In this demo, the [graph diameter](http://mathworld.wolfram.com/GraphDiameter.html) (i.e., the length of the longest shortest path or the longest graph geodesic) of a cellular compartment is computed for a neuron fetched from the MouseLight database.
+SNT features a script recorder that similarly to _ImageJ's macro recorder_ converts menu and button clicks into executable code. Note however that while the recorder captures simple commands well, it struggles to capture those that are more complex or particularly interactive.
-- **Reconstruction\_Viewer\_Demo.py** Exemplifies how to render reconstructions and neuropil annotations in a stand-alone [Reconstruction Viewer](/plugins/snt/reconstruction-viewer).
+The goal of the recorder is twofold: 1) simplify prototyping of new scripts and 2) Log your actions during a tracing session. This is particularly useful to assemble reproducible records.
-- **SciView\_Demo.groovy** Exemplifies how bridge SNT with [sciview](/plugins/sciview).
+There are two ways to start the recorder: {% include bc path='Scripts|New|Record...'%} or by pressing the _Record_ button in [Command Palette](/plugins/snt/manual#command-palette).
-- **Extensive\_Sholl\_Stats.groovy** Exemplifies how to perform linear and polynomial regression on tabular [Sholl](/plugins/sholl-analysis) data.
+As a rule-of-thumb, commands that are simple or do not involve prompts record flawlessly. This includes setting filters for visibility of tags, applying Tags, or filtering paths in the Path Manager. Commands for fully automated reconstructions, or generating secondary layers _should_ work well. However, many others remain limited.
-### Boilerplate
-
-These scripts hold extensible boilerplate code in several programming languages, namely [BeanShell](/scripting/beanshell), [Groovy](/scripting/groovy) and [Jython](/scripting/jython). The most essential imports and [script parameters](/scripting/parameters) are included to facilitate rapid development.
-
-### Tracing
-
-- **Scripted\_Tracing\_Demo.py** Exemplifies how to programmatically perform A\* tracing between two points without GUI interaction, which allows for automated tracing of relatively simple structures (e.g., neurospheres neurites, microtubule bundles, etc). In this demo, points are retrieved from the SWC file of SNT's "demo tree", effectively recreating the initial SWC data.
-
-- **Scripted\_Tracing\_Demo\_(Interactive).py** Exemplifies how to programmatically interact with a running instance of SNT to perform auto-tracing tasks.
-
-- **Take\_Snapshot.py** Displays a WYSIWYG image of a tracing canvas. Exemplifies how to script SNT using SNTService.
-
-### Batch
-
-This menu hosts scripts that process files in bulk. Namely:
+
+
+
-You may notice that, by default, the cursor [snaps](/plugins/snt/manual#auto-snapping) to the brightest pixel in its vicinity. If you prefer to manually control the placement of nodes, feel free to toggle feature by pressing {% include key key='S' %}. Now, to begin tracing, move through the image stack to find the start point of a path then click there with the left mouse button.
+You may notice that, by default, the cursor [snaps](/plugins/snt/manual#cursor-auto-snapping) to the brightest pixel in its vicinity. If you prefer to manually control the placement of nodes, feel free to toggle this feature by pressing {% include key key='S' %}. Now, to begin tracing, move through the image stack to find the start point of a path then click there with the left mouse button.
### II. Pick A Subsequent Point
@@ -26,13 +31,16 @@ You may notice that, by default, the cursor [snaps](/plugins/snt/manual#auto-sna
A small circle should appear, highlighting the start of the path. Move through the stack to find a subsequent point further along the same structure to be traced (neuron, blood vessel, etc.), and click there.
If a path between the two points cannot be found immediately, you may see the animated progress of the search. You can scroll through the stack while such a search progresses: If it appears to not be making good progress, it's probably best to press the "Cancel/Esc" button (shortcut: {% include key key='C' %}/{% include key key='Esc' %}) and pick a point closer to the start point.
-
-Note that increasing *Z* in the *Cursor Auto-snapping* panel allows for automated Z-navigation on signal mouseover.
+NB:
+- Increasing *Z* in the *Cursor Auto-snapping* panel allows for automated Z-navigation on signal mouseover
+- You can increase the contrast (opacity, size, etc.) of Path nodes in the _Path rendering_ widget of the [Options tab](/plugins/snt/manual#options-tab)
+
+
### III. Confirm The Temporary Segment
-Once the search has reached the target point, the path is shown in cyan (to indicate that this is still a temporary path) and you are asked to confirm (by clicking "Yes" or pressing {% include key key='Y' %}) that this path is following the route through the image that you expect. If it is not, then click "No" {% include key key='N' %} and you'll go back to the [previous step](#ii-picking-a-subsequent-point). Assuming you confirmed the path, the confirmed path will appear in red. Now you are essentially back at [step II](#ii-picking-a-subsequent-point). Normally you will go on to pick further points along the structure. However, if you have finished with that path, click "Finish Path" {% include key key='F' %} and you will go back to [step I](#i-picking-a-start-point). If you completed that path it would be shown in magenta.
+Once the search has reached the target point, the path is shown in cyan (to indicate that this is still a temporary path) and you are asked to confirm (by clicking "Yes" or pressing {% include key key='Y' %}) that this path is following the route through the image that you expect. If it is not, then click "No" {% include key key='N' %} and you'll go back to the [previous step](#ii-pick-a-subsequent-point). Assuming you confirmed the path, the confirmed path will appear in red. Now you are essentially back at [step II](#ii-pick-a-subsequent-point). Normally you will go on to pick further points along the structure. However, if you have finished with that path, click "Finish Path" {% include key key='F' %} and you will go back to [step I](#i-pick-a-start-point). If you completed that path it would be shown in magenta.
@@ -40,20 +48,23 @@ Once the search has reached the target point, the path is shown in cyan (to indi
-To select the path you want to branch off from, you can either select it in the Path Manager, or press {% include key key='G' %} while the mouse pointer is near the path. When the path is first selected, it will be shown in the default green color.
+To select the path you want to branch off from, you can either select it in the Path Manager, or press {% include key key='G' %} while the mouse pointer is near the path. When the path is first selected, it will be shown in the default green color. Note that you can also right-click on the image and choose _Select Paths by 2D ROI_ from the contextual menu: This will allow you to draw coarsely around the path of interest to activate it.
### II. Select The Fork Point
-To force the start of the new path to be a branch of the selected path, hold down the {% include key keys='Alt|Shift' %} keys while you move the mouse to find the branch point under the red cross-hairs, now decorated with a "Fork Point" annotation. With {% include key keys='Alt|Shift' %} held down, click with the left mouse button.
-
+To force the start of the new path to be a branch of the selected path, hold down the {% include key keys='Alt|Shift' %} keys while you move the mouse to find the branch point under the red cross-hairs, now decorated with a "Fork Point" annotation. With {% include key keys='Alt|Shift' %} held down, click with the left mouse button. Finally, release the keys.
-
-Finally, release the keys. Note that it is also possible to zoom into the branch point, right-click on the image and choose *Fork at Nearest Node* from the contextual menu.
+NB:
+- It is also possible to zoom into the branch point, right-click on the image and choose *Fork at Nearest Node* from the contextual menu
+- The forking shortcut can also be simplified (_Temporary Paths_ section of the [Options tab](/plugins/snt/manual#options-tab))
### III. Extend The Path
@@ -71,7 +82,7 @@ From this point on, you can carry on adding nodes to the branched path as [above
|
Supposing you want the end of a path that you're tracing to join onto an existing path, you just use the same modifier key when selecting the end point of the last part of the path. To go into that in more detail, if you're halfway through tracing a path like [1]: |
@@ -84,7 +95,7 @@ From this point on, you can carry on adding nodes to the branched path as [above
|||||||||
|
... and you want the final part of that path to join up with the existing path running from the top-left to top-right of the image. First, select that path in the path list (or using the {% include key key='G' %} shortcut) as in [2]: |
@@ -97,7 +108,7 @@ From this point on, you can carry on adding nodes to the branched path as [above
|||||||||
|
Now hold down {% include key keys='Alt|Shift' %} to restrict the endpoint to be a "join" on that existing path. Click (while still holding down the modifier keys) to start the search for that endpoint and make it join the existing path. If the search can find a path to the end point, the result should look like [3]: |
@@ -110,7 +121,7 @@ From this point on, you can carry on adding nodes to the branched path as [above
|||||||||
|
If you're happy with the result, confirming the temporary path will automatically complete the whole path, since if you're creating an end join there cannot be any more to the path. Note that the path list indicates that this new Path (1) ends on the existing Path (0). The result will look like [4]: |
@@ -147,26 +158,30 @@ If both nodes are terminal, the paths are merged together. Otherwise, one path w
## Tracing in the Legacy 3D Viewer
-### I.Starting the Viewer
+### I. Starting the Viewer
|
Accurate node placement requires XY, ZY and XZ views to be visible. You can do so at startup, by making sure that Default: XY, ZY and XZ views is selected, or by clicking in Display ZY/XZ Views in the Options tab if you have already started SNT. |
@@ -189,7 +202,7 @@ This section describes methods to increase the accuracy of node placement.
|
|
Find the approximate location of your start point by moving your mouse in the XY window, holding down {% include key key='Shift' %} to synchronize the view in the other panes. At this point, you should enable cursor auto-snapping in the Main tab using suitable parameters for your image. When this option is enabled, the cursor will automatically 'sniff' for local maxima and 'snap' to their average X,Y,Z position. The pixel that is most likely to be on a neurite is indicated by the red cross-hair cursor. @@ -198,9 +211,9 @@ This section describes methods to increase the accuracy of node placement.
|
|
|
- When you press {% include key key='+' %} to zoom in, all the panes will zoom in on the point that the crosshair is over, so each time you press {% include key key='+' %}, make sure you move your mouse pointer over the neurire so that it's still over the structure of interest. You may want to adjust in the Views widget (Options tab) whether all views should zoom synchronously. When you press {% include key key='+' %} to zoom in, all the panes will zoom in on the point that the crosshair is over, so each time you press {% include key key='+' %}, make sure you move your mouse pointer over the neurite so that it's still over the structure of interest. You may want to adjust in the Views widget (Options tab) whether all views should zoom synchronously. Note that when Z-snapping is enabled, all views become synchronized, |
@@ -208,7 +221,7 @@ This section describes methods to increase the accuracy of node placement.
|
|
Locate the center of the structure to be clicked on. If cursor auto-snapping is enabled, simply mouse over the structure, otherwise, try moving the mouse and scroll wheel in each of the panes (holding down {% include key key='Shift' %} so synchronize the views in all three panes). Note that you can toggle the cursor auto-snapping feature at will, by pressing the shortcut {% include key key='S' %}. Also, note that you can "click" on the brightest voxel of a voxel column, by pressing {% include key key='M' %}. When you're happy with the point under the crosshairs, left-click to start the path: @@ -217,7 +230,7 @@ This section describes methods to increase the accuracy of node placement.
|
|
|
Zoom out again with the {% include key key='-' %} key, and similarly zoom in on the next point you want to be on your path to place it precisely: |
@@ -225,7 +238,7 @@ This section describes methods to increase the accuracy of node placement.
|
|
The path along the neuron may not follow the center line perfectly: |
@@ -233,7 +246,7 @@ This section describes methods to increase the accuracy of node placement.
|
|
... but you can later improve that with the {% include bc path='Refine/Fit|Fit Path...'%} option in the Path Manager, which tries to align the path to the midline of the structure to sub-voxel accuracy: |
@@ -241,42 +254,128 @@ This section describes methods to increase the accuracy of node placement.
|
| - | - |
+
+Paths can be "filled out" to volumes, i.e., converted into 3D images that can be used to improve the visualization of the shape of a neuron beyond what can be seen from traced center-lines, and/or subsequent image processing routines. The filling algorithm uses the center-line path coordinates as seeds in a 'signal search' that expands along neurites to encapsulate the neurite in 3D. The result can be exported as different types of images, including distance maps, binary masks or labeled image.
-
-There is a simple facility in this plugin for "filling out" paths to volumes. This is not particularly sophisticated, but often good enough for a rough visualization of the shape of a neuron beyond what can be seen from the traced path.
+Fillings are controlled by the Fill Manager and share many of the same properties of auto-tracing:
+
+- Fillings can be performed on the main image or secondary tracing layer
+
+- The same cost function used in auto-tracing is used for filling
-### I.Starting the Fill
+- Fillings will be more accurate once SNT is aware of properties of the image being traced, so before filling imported paths you may need to re-trace a representative neurite (you can discard the result)
-First, select the one or more paths that you want to fill out from in the Path Manager and select {% include bc path="Fill | Fill Out..." %} in the Path Manager menu options. The selected paths are shown in green so that you can check that you're starting from the right ones. After a couple of seconds if you scroll through the stack you should be able to see a thick green surround the path:
-The filler continues to explore the image starting from the path until you click "Pause" or "Stop" in the dialog. However, the fill which is shown only includes those points up to a certain threshold distance from the path. (Note that in this section "distance" doesn't mean a real physical distance, but a measure which takes into account the intensity values of the pixels which must be passed through when moving away from the path.) Information about the current threshold and the progress of the search is shown in the dialog.
+### I. Starting the Fill
+First, select the one or more paths that you want to fill out from in the Path Manager and select {% include bc path="Fill|Fill Out..." %} in the Path Manager (or select none if you want to fill all the existing paths). Once the filling starts, you should be able to see a thick green surround the path while scrolling through the 3D stack:
+
+The filler continues to explore the image until you click "Pause" or "Stop" in the dialog, or until all the image has been fully explored. However, the fill which is shown only includes those points up to a certain threshold distance from the path. Note that this "distance" doesn't mean a real physical distance, but instead a 'likelihood-distance': a measure which takes into account the intensity values of the pixels which must be passed through when moving away from the path. Information about the current threshold and the progress of the search is shown in the dialog. Note that if your image is rather small, the entire image may be fully explored before you have time to interact with prompt.
+
The "Cursor position:" state under "Search Status" is updated as you move your mouse over the image. If the point under the mouse has been reached by the search then it will show you that point's distance from the path. Otherwise, it will read "Not reached by search yet".
-
-Two lines above, the "Current threshold distance:" shows your current threshold distance: so if this is set to 0.2 then that means that all points less than 0.2 from the path are included in the fill (and shown in green in the image.) The "Max. explored distance:" state under this line shows the maximum distance from the path that has been completely explored.
+The _Search status_ shows your current threshold distance: so if this is set to 0.2 then that means that all points less than 0.2 from the path are included in the fill (and highlighted in green in the image). The "Max. explored distance:" shows the maximum distance from the path that has been completely explored.
### II.Adjusting the Fill Threshold
You can change the fill threshold in one of three ways:
-- Clicking on a point in the image that has been reached by the search (This is the most intuitive way of altering the threshold). It may be helpful to disable the "Enable Snapping within: XY-Z" feature for the cursor while doing this.
+- Clicking on a point in the image that has been reached by the search (This is the most intuitive way of altering the threshold). It may be helpful to disable the "Enable Snapping within: XY-Z" feature for the cursor while doing this
+
- Manually changing the threshold in the "Specify manually:" input box and clicking the "Apply" button beside it.
+
- Clicking the "Use explored maximum" button below the threshold input box and click "Apply", which sets the threshold to the maximum explored distance (the value shown in "Max. explored distance:" under the "Search Status" dialog).
-Anyway, assuming that you want to use the first of these approaches, you should use the approach described below. It is difficult to set the threshold accurately from the image unless you zoom in, so first zoom on part of the path that you want to set the threshold for.
+We will assume that you want to use the first of these approaches:
-Since the solid green fill obscures the intensity value of the points in the fill, I suggest that you switch to the semi-transparent view of the fill at this stage by selecting the "Transparent overlay" option in the "Rendering Options" dialog. Note that this may slow down filling.
+- It is difficult to set the threshold accurately from the image unless you zoom in, so first zoom on part of the path that you want to set the threshold for.
-As you can see in the middle image, the threshold is set too far from the path, since there are many completely dark points under the green fill, as well as points on different paths than those of interest. Experiment with clicking on different points closer to the path in order to adjust the threshold until you are happy with it. You might end up with something like the rightmost image:
+- Since the solid green fill obscures the intensity value of the points in the fill, you may want to activate the _Transparent overlay_ checkbox. Note that this _could_ slow down filling, although the performance hit is usually negligible.
+
+- As you can see in the middle image, the threshold is set too far from the path, since there are many background voxels under the green fill, as well as voxels on different paths than those of interest. Experiment with clicking on different locations closer to the path in order to adjust the threshold until you are satisfied with thr result. You might end up with something like the rightmost image:
@@ -284,51 +383,38 @@ As you can see in the middle image, the threshold is set too far from the path,
-
-
- 
+ 
-
It remains possible to trace in the legacy 3D Viewer. To open it, select the *3D* menu tab in the SNT dialog and look for *Legacy 3D Viewer*. You will see 3 parameters:
- Select *New with image* from the *Viewer* drop-down menu (selecting *New without image* would only allow you to look at reconstructions without the underlying signal). Note that you can recycle existing viewers you may have open by choosing their window titles from the drop-down menu.
+
- Select the preferred rendering style from the *Mode* drop-down menu.
+
- Once you *Apply* the viewer choice, a prompt will appear asking you to choose the resampling factor for the image. Then, the viewer window will appear with the currently open image.
-### II.Tracing and Navigation
+### II. Tracing and Navigation
-- **Selecting points for tracing** Select the *Wand tool* ({% include key key='W' %} [shortcut](/plugins/snt/key-shortcuts#legacy-3d-viewer)) in the main ImageJ toolbar and click over the region you want to trace. Tracing works the same way as in the 2.5D view, i.e., click somewhere in the image to create a starting point, then click further along the structure of interest to find a path between the two points, then confirm or deny the temporary segment as described [above](#Tracing). Similarly, branching occurs as [described for 2D canvas(es)](#Branching:_Start_A_Path_On_An_Existing_Path), by holding the {% include key keys='Alt|Shift' %} modifier.
+- **Selecting points for tracing** Select the *Wand tool* ({% include key key='W' %} [shortcut](/plugins/snt/key-shortcuts#legacy-3d-viewer)) in the main ImageJ toolbar and click over the region you want to trace. Tracing works the same way as in the 2.5D view, i.e., click somewhere in the image to create a starting point, then click further along the structure of interest to find a path between the two points, then confirm or deny the temporary segment as described [above](#Tracing). Similarly, branching occurs as [described for 2D canvas(es)](#branching-start-a-path-on-an-existing-path), by holding the {% include key keys='Alt|Shift' %} modifier.
-- **Rotation** Either use the *Hand tool* ({% include key key='H' %} [shortcut](/plugins/snt/key-shortcuts#legacy-3d-viewer)) tool and left-click while dragging the mouse or drag mouse while holding the scroll wheel.
+- **Rotation** Either use the *Hand tool* ({% include key key='H' %} [shortcut](/plugins/snt/key-shortcuts#legacy-3d-viewer)) tool and left-click while dragging the mouse or drag mouse while holding the scroll wheel
+
- **Translation** Hold {% include key key='Shift' %} and the scroll wheel while dragging the mouse.
+
- **Adjusting zoom depth** Scroll the mouse wheel.
Once you have selected each of these tools (Wand and Hand) once, you should be able to switch between them by pressing the {% include key key='Esc' %} key. See [Key Shortcuts](/plugins/snt/key-shortcuts#legacy-3d-viewer) for the list of all supported shortcuts.
@@ -175,13 +190,11 @@ Once you have selected each of these tools (Wand and Hand) once, you should be a
-# Accurate Point Placement
-
-This section describes methods to increase the accuracy of node placement.
-
+## Accurate Point Placement
+{% include notice icon="info" content=op1-demo-incomplete %}
