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Going through QC (available on this link), in most cases, the false positive lesion segmentation corresponds to the central canal (filled with cerebrospinal fluid). In a few other subjects, some hyperintense cord areas or areas with low signal were segmented.
QC GIF
Next steps
Improve the model to lower the number of false positive segmentations.
Idea: include spine-generic subjects (with empty lesion GT) in the training set to teach the model not to segment the spinal canal.
The text was updated successfully, but these errors were encountered:
Description
I tested SCIsegV2 (as part of SCT v6.4) on healthy subjects from spine-generic data-multi-subject to assess the number of false positive lesion segmentations.
Script
Script used: baselines/run_inference_spine-generic.sh
Results
The model predicted some sort of lesion in 34 of 267 subjects (~12%); see the list below.
list of subjects
The loop using get_unique_values to get the subjects with non-zero lesion masks:
Going through QC (available on this link), in most cases, the false positive lesion segmentation corresponds to the central canal (filled with cerebrospinal fluid). In a few other subjects, some hyperintense cord areas or areas with low signal were segmented.
QC GIF
Next steps
Improve the model to lower the number of false positive segmentations.
Idea: include spine-generic subjects (with empty lesion GT) in the training set to teach the model not to segment the spinal canal.
The text was updated successfully, but these errors were encountered: