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dicom_converter.py
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dicom_converter.py
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# -*- coding: utf-8 -*-
"""
Created on Mon Mar 21 2022
@author: Riccardo Gambino
"""
"""
Bruker To Dicom file converter with both
traditional and multicore processing.
"""
# from lib2to3.pytree import convert
from multiprocessing import Pool, cpu_count
import os, sys, traceback, re, time
# from threading import Thread
from glob import glob
import numpy as np
import shutil
from read_visupars import read_visupars_parameters
from cest_dict import add_cest_dict
from read_method import read_method_parameters
from tkinter import messagebox
from pydicom.dataset import Dataset, FileDataset
import pydicom.uid
import dateutil.parser
import datetime
def scan_directory(directory):
list_dirs = sorted(os.listdir(directory))
return list_dirs
def check_and_create(directory):
if not os.path.isdir(directory):
os.makedirs(directory)
class Bruker2DicomConverter():
def __init__(self, params):
self.n_processes = int(cpu_count() - 1)
if 'results_flag' in params:
self.results_flag = params['results_flag']
else:
self.results_flag = 0
def get_list_of_folders(self, folder_to_convert, dst_folder):
list_dirs = scan_directory(folder_to_convert)
new_list_dirs = []
for dir in list_dirs:
current_path = os.path.join(folder_to_convert, dir).replace('\\', '/')
current_dst = os.path.join(dst_folder, 'MR', dir).replace('\\', '/')
if os.path.isdir(current_path):
if 'Results' in dir and self.results_flag == 1:
new_list_dirs.append((current_path, current_dst))
else:
dseq_file = glob(current_path + '/**/2dseq', recursive=True)
if dseq_file != []:
new_list_dirs.append((current_path, current_dst))
elif 'Custom' in dir:
new_list_dirs.append((current_path, current_dst))
return new_list_dirs
def multi_core_conversion(self, folder_to_convert, dst_folder):
list_dirs = self.get_list_of_folders(folder_to_convert, dst_folder)
start_time = time.time()
print('Converting ' + str(folder_to_convert.split('/')[-1]))
with Pool(processes=self.n_processes) as pool:
pool.map(self.convert, list_dirs)
end_time = time.time()
print('Elapsed time for conversion: ' + str(end_time - start_time) + ' s')
def start_conversion(self, folder_to_convert, dst_folder):
list_dirs = self.get_list_of_folders(folder_to_convert, dst_folder)
start_time = time.time()
parameters = 0
PV_version = ''
for i, dirs in enumerate(list_dirs, 1):
self.convert(dirs)
end_time = time.time()
print('Elapsed time for conversion: ' + str(end_time - start_time) + ' s')
def convert(self, dirs):
print('Starting with ' + str(dirs[0].split('/')[-1]))
convert_path = dirs[0]
dst_path = dirs[1]
if 'Results' in dirs[0].split('/')[-1]:
shutil.copytree(convert_path, dst_path)
elif 'Custom' in dirs[0].split('/')[-1]:
check_and_create('/'.join(dst_path.split('/')[:-1]))
shutil.copy(convert_path, dst_path)
else:
dseq_file = glob(convert_path + '/**/2dseq', recursive=True)
dseq_path = dseq_file[0].replace('\\', '/')
# Visu_pars file
visu_pars_path = glob(convert_path + '/**/**/visu_pars', recursive=True)[0].replace('\\', '/')
with open(visu_pars_path, "r"):
parameters = read_visupars_parameters(visu_pars_path)
# Reco file
reco_path = '/'.join(dseq_path.split('/')[:-1]) + '/' + "reco"
with open(reco_path, "r"):
reco_parameters = read_method_parameters(reco_path)
# Method file
method_path = convert_path + '/' + "method"
with open(method_path, "r"):
method_parameters = read_method_parameters(method_path)
# acqp file
acqp_path = convert_path + '/' + "acqp"
with open(acqp_path, "r"):
acqp_parameters = read_visupars_parameters(acqp_path)
try:
PV_version = parameters.get("VisuCreatorVersion")
if PV_version == '':
PV_version = acqp_parameters.get("ACQ_sw_version")
except Exception as e:
messagebox.showerror("XNAT-PIC - Bruker2Dicom", e)
exc_type, exc_value, exc_traceback = sys.exc_info()
traceback.print_tb(exc_traceback)
sys.exit(1)
filename_little_endian = "MRIm"
img_type = parameters.get("VisuCoreWordType")
img_endianness = parameters.get("VisuCoreByteOrder")
img_frames = parameters.get("VisuCoreFrameCount")
img_dims = parameters.get("VisuCoreSize")
core_ext = parameters.get("VisuCoreExtent")
if isinstance(parameters.get("VisuCoreDataSlope"), str) and isinstance(parameters.get("VisuCoreDataOffs"), str):
slope = float(parameters.get("VisuCoreDataSlope")[parameters.get("VisuCoreDataSlope").find('(') \
+ 1 : parameters.get("VisuCoreDataSlope").find(')')])
intercept = float(parameters.get("VisuCoreDataOffs")[parameters.get("VisuCoreDataOffs").find('(') \
+ 1 : parameters.get("VisuCoreDataOffs").find(')')])
else:
slope = parameters.get("VisuCoreDataSlope")
intercept = parameters.get("VisuCoreDataOffs")
# Check endianness and precision
if img_type == "_32BIT_SGN_INT" and img_endianness == "littleEndian":
data_precision = np.dtype("<i4")
elif img_type == "_32BIT_SGN_INT" and img_endianness == "bigEndian":
data_precision = np.dtype(">i4")
elif img_type == "_16BIT_SGN_INT" and img_endianness == "littleEndian":
data_precision = np.dtype("<i2")
elif img_type == "_16BIT_SGN_INT" and img_endianness == "bigEndian":
data_precision = np.dtype(">i2")
else:
messagebox.showerror(
"Error!", "Image data precision is neither 16 nor 32 bit!"
)
os._exit(0)
raw_data = open(dseq_path, "rb")
img_data_precision = np.fromfile(raw_data, dtype=data_precision)
raw_data.close()
check_and_create(dst_path)
os.chdir(dst_path)
if img_type == "_16BIT_SGN_INT" and img_endianness == "littleEndian":
# img = np.array(img_data_precision,np.uint16)
if np.size(slope) == 1:
img_data_corrected = img_data_precision * slope
img_data_corrected += intercept
else:
img_data_corrected = img_data_precision * slope[0]
img_data_corrected += intercept[0]
factor = ((2 ** 16) - 1) / (np.amax(img_data_corrected))
img_float = img_data_corrected * factor
img = np.array(img_float, np.uint16)
# if 32 bit, slope and intercept correction
elif img_type == "_32BIT_SGN_INT" and img_endianness == "littleEndian":
if np.size(slope) == 1:
img_data_corrected = img_data_precision * slope
img_data_corrected += intercept
else:
img_data_corrected = img_data_precision * slope[0]
img_data_corrected += intercept[0]
factor = ((2 ** 16) - 1) / (np.amax(img_data_corrected))
img_float = img_data_corrected * factor
img = np.array(img_float, np.uint16)
else:
messagebox.showerror(
"Error!",
"The image you are trying to convert is neither 16 bit nor 32 bit!",
)
os._exit(0)
# Populate required values for file meta information
file_meta = Dataset()
file_meta.MediaStorageSOPClassUID = "1.2.840.10008.5.1.4.1.1.4"
file_meta.MediaStorageSOPInstanceUID = parameters.get("VisuUid")
file_meta.ImplementationClassUID = "1.2.276.0.7230010.3.0.3.5.3"
file_meta.ImplementationVersionName = 'OFFIS_DCMTK_353'
# Create the FileDataset instance (initially no data elements, but file_meta supplied)
img_data = FileDataset(filename_little_endian, {}, file_meta=file_meta, preamble=b"\0" * 128)
img_data.file_meta.TransferSyntaxUID = pydicom.uid.ExplicitVRLittleEndian
# This group is responsible for describing how to read the pixels
nframes = int(parameters.get("VisuCoreFrameCount"))
img_data.NumberOfFrames = parameters.get("VisuCoreFrameCount")
img_data.SamplesPerPixel = 1
img_data.PhotometricInterpretation = "MONOCHROME2"
img_data.PixelRepresentation = 0 # unsigned (0)
img_data.BitsAllocated = 16
img_data.BitsStored = 16
img_data.HighBit = 15
img_data.Columns = int(img_dims[0])
img_data.Rows = int(img_dims[1])
img_data.PixelSpacing = [core_ext[0]/img_dims[0], core_ext[1]/img_dims[1]]
img_data.WindowCenterWidthExplanation = "MinMax"
# PixelData contains the raw bytes exactly as found in the file
img_data.PixelData = img.tobytes()
img_data[0x7FE0, 0x0010].VR = "OW"
# The dicom_dict entry for LargestImagePixelValue uses an ambiguous VR (Value Representation).
# It can either be an unsigned short integer (US) or a signed short integer (SS).
# In order to properly write the data to the file,
# you have to explicitly tell it which one you want to use.
img_data.WindowWidth = int(np.amax(img) + 1)
img_data.WindowCenter = int((np.amax(img) + 1) / 2)
img_data[0x0028, 0x1050].VR = "DS"
img_data[0x0028, 0x1051].VR = "DS"
img_data.SmallestImagePixelValue = int(np.amin(img_data.pixel_array))
img_data.LargestImagePixelValue = int(np.amax(img_data.pixel_array))
img_data[0x0028, 0x0106].VR = "US"
img_data[0x0028, 0x0107].VR = "US"
add_cest_dict()
# Loop over the number of frames found in img_data
for iteration, layer in enumerate(img_data.pixel_array, 0):
layer = np.reshape(layer, int(img_dims[0]) * int(img_dims[1]))
# Populate required values for file meta information
file_meta_temp = Dataset()
file_meta_temp.MediaStorageSOPClassUID = "1.2.840.10008.5.1.4.1.1.4"
file_meta_temp.MediaStorageSOPInstanceUID = parameters.get("VisuUid") + ".%s" % (iteration)
file_meta_temp.ImplementationClassUID = "1.2.276.0.7230010.3.0.3.5.3"
file_meta_temp.ImplementationVersionName = 'OFFIS_DCMTK_353'
# Create the FileDataset instance (initially no data elements, but file_meta supplied)
ds_temp = FileDataset(filename_little_endian, {}, file_meta=file_meta_temp, \
preamble=b"\0" * 128)
ds_temp.file_meta.TransferSyntaxUID = pydicom.uid.ExplicitVRLittleEndian
# Add the data elements - Check DICOM standard
ds_temp.ImageType = ["ORIGINAL", "PRIMARY", "OTHER"]
# if ('treated' in root):
# appendix='treated'
# elif ('untreated' in root):
# appendix='untreated'
# patient_type=re.findall('/[^/]*trea[^/]*/[^/]*/',root)
# if len(patient_type)!=0:
# group=patient_type[0].split('/')[1]
# timepoint=patient_type[0].split('/')[2]
# ds.PatientName = parameters.get("VisuSubjectName")+'_'+group+'_'+timepoint
# else:
# ds.PatientName= parameters.get("VisuSubjectName")
# head_ID, _ = os.path.split(head2)
############### Get common parameters among PV versions ###################
ds_temp.PatientName = parameters.get("VisuSubjectName")
ds_temp.PatientID = parameters.get("VisuSubjectId")
ds_temp.PatientBirthDate = parameters.get("VisuSubjectBirthDate")
ds_temp.PatientSex = parameters.get("VisuSubjectSex")
ds_temp.PatientWeight = parameters.get("VisuSubjectWeight")
ds_temp.PatientComments = parameters.get("VisuSubjectComment")
ds_temp.PatientSpeciesDescription = parameters.get("VisuSubjectType")
ds_temp.ReferringPhysicianName = ' '.join(parameters.get("VisuStudyReferringPhysician"))
ds_temp.PatientBreedDescription = None
ds_temp.PatientBreedCodeSequence = None
ds_temp.ResponsiblePerson = None
ds_temp.BreedRegistrationSequence = None
ds_temp.ResponsibleOrganization = ' '.join(parameters.get("VisuInstitution"))
ds_temp.StudyID = parameters.get("VisuStudyId")
ds_temp.SeriesNumber = os.path.basename(convert_path)
ds_temp.Modality = str("MR")
ds_temp.ScanningSequence = str("RM")
ds_temp.SequenceVariant = str("None")
ds_temp.SequenceName = ' '.join(parameters.get("VisuAcqSequenceName"))
ds_temp.ProtocolName = parameters.get("VisuAcquisitionProtocol")
ds_temp.SeriesDescription = parameters.get("VisuAcquisitionProtocol")
if np.size(parameters.get("VisuAcqRepetitionTime")) > 1 and np.size(parameters.get("VisuAcqRepetitionTime")) == nframes:
ds_temp.RepetitionTime = float(np.array(parameters.get("VisuAcqRepetitionTime"), dtype=int)[iteration])
elif np.size(parameters.get("VisuAcqRepetitionTime")) > 1 and np.size(parameters.get("VisuAcqRepetitionTime")) != nframes:
r_step = int(nframes/np.size(parameters.get("VisuAcqRepetitionTime")))
repetition_time = []
for t in range(0,np.size(parameters.get("VisuAcqRepetitionTime"))):
for kk in range(0,r_step):
repetition_time.append(parameters.get("VisuAcqRepetitionTime")[t])
ds_temp.RepetitionTime=float(np.array(repetition_time,dtype=float)[iteration])
else:
ds_temp.RepetitionTime=float(parameters.get("VisuAcqRepetitionTime"))
if np.size(parameters.get("VisuAcqEchoTime")) > 1 and np.size(parameters.get("VisuAcqEchoTime")) == nframes:
ds_temp.EchoTime=str(np.array(parameters.get("VisuAcqEchoTime"),dtype=float)[iteration])
elif np.size(parameters.get("VisuAcqEchoTime")) > 1 and np.size(parameters.get("VisuAcqEchoTime")) != nframes:
e_step = int(nframes/np.size(parameters.get("VisuAcqEchoTime")))
echo_time = []
for t in range(0,np.size(parameters.get("VisuAcqEchoTime"))):
for kk in range(0,e_step):
echo_time.append(parameters.get("VisuAcqEchoTime")[t])
ds_temp.EchoTime=str(np.array(echo_time,dtype=float)[iteration])
else:
ds_temp.EchoTime=parameters.get("VisuAcqEchoTime")
ds_temp.AcquisitionDuration=parameters.get("VisuAcqScanTime")
ds_temp.NumberOfAverages = str(parameters.get("VisuAcqNumberOfAverages"))
ds_temp.ImagingFrequency = parameters.get("VisuAcqImagingFrequency")
ds_temp.ImagedNucleus = parameters.get("VisuAcqImagedNucleus")
ds_temp.NumberOfPhaseEncodingSteps = parameters.get("VisuAcqPhaseEncSteps")
ds_temp.EchoTrainLength = parameters.get("VisuAcqEchoTrainLength")
ds_temp.PixelBandwidth = parameters.get("VisuAcqPixelBandwidth")
ds_temp.FlipAngle = str(parameters.get("VisuAcqFlipAngle"))
ds_temp.PatientPosition = parameters.get("VisuSubjectPosition")
ds_temp.PatientOrientation = method_parameters.get("PVM_SPackArrReadOrient")[0][1:]
ds_temp.StationName = parameters.get("VisuStation")
ds_temp.InstitutionName = " ".join(parameters.get("VisuInstitution"))
ds_temp.Manufacturer = parameters.get("ORIGIN")
ds_temp.SeriesInstanceUID = parameters.get("VisuUid")
ds_temp.FrameOfReferenceUID = parameters.get("VisuUid") + ".%s" % (iteration)
ds_temp.StudyInstanceUID = parameters.get("VisuStudyUid")
ds_temp.SOPInstanceUID = parameters.get("VisuUid") + ".%s" % (iteration)
ds_temp.SOPClassUID = "1.2.840.10008.5.1.4.1.1.4"
ds_temp.AcquisitionNumber = iteration + 1
ds_temp.InstanceNumber = iteration + 1
ds_temp.MRAcquisitionType = str(parameters.get("VisuCoreDim")) + "D"
ds_temp.SoftwareVersions = str(parameters.get("VisuCreator")) + " " + str(parameters.get("VisuCreatorVersion"))
ds_temp.PercentPhaseFieldOfView = "100"
if parameters.get("VisuCoreOrientation").shape[0] == 1:
ds_temp.ImagePositionPatient = list(map(str, parameters.get("VisuCorePosition")[0]))
ds_temp.ImageOrientationPatient = list(map(str, parameters.get("VisuCoreOrientation")[0][0:6]))
ds_temp.SliceThickness = parameters.get("VisuCoreFrameThickness")
ds_temp.NumberOfFrames = 1
ds_temp.ImagesInAcquisition = parameters.get("VisuCoreFrameCount")
ds_temp.SliceLocation = parameters.get("VisuCorePosition")[0][2]
elif parameters.get("VisuCoreOrientation").shape[0] != nframes:
p = int(nframes / parameters.get("VisuCorePosition").shape[0])
visucoreposition = np.tile(parameters.get("VisuCorePosition"), (p, 1))
visucoreorientation = np.tile(parameters.get("VisuCoreOrientation"), (p, 1))
ds_temp.ImagePositionPatient = list(map(str, visucoreposition[iteration - 1]))
ds_temp.ImageOrientationPatient = list(map(str, visucoreorientation[iteration - 1][0:6]))
ds_temp.SliceThickness = parameters.get("VisuCoreFrameThickness")
ds_temp.NumberOfFrames = 1
ds_temp.ImagesInAcquisition = parameters.get("VisuCoreFrameCount")
ds_temp.SliceLocation = list(map(str, visucoreposition[iteration]))[2]
else:
ds_temp.ImagePositionPatient = list(map(str, parameters.get("VisuCorePosition")[iteration - 1]))
ds_temp.ImageOrientationPatient = list(map(str, parameters.get("VisuCoreOrientation")[iteration - 1][0:6]))
ds_temp.SliceThickness = parameters.get("VisuCoreFrameThickness")
ds_temp.NumberOfFrames = 1
ds_temp.ImagesInAcquisition = parameters.get("VisuCoreFrameCount")
ds_temp.SliceLocation = list(map(str, parameters.get("VisuCorePosition")[iteration - 1]))[2]
# Get other parameters which differ among PV versions
if PV_version == "5.1":
########################### ParaVision 5.1 ##############################
studydate = parameters.get("VisuStudyDate").date()
studytime = parameters.get("VisuStudyDate").time()
ds_temp.StudyDate = studydate.strftime("%Y%m%d")
ds_temp.StudyTime = studytime.strftime("%H%M%S")
acquisitiondate = parameters.get("VisuAcqDate").date()
acquisitiontime = parameters.get("VisuAcqDate").time()
ds_temp.AcquisitionDate = acquisitiondate.strftime("%Y%m%d")
ds_temp.AcquisitionTime = acquisitiontime.strftime("%H%M%S")
VisuAcqImagePhaseEncDir = parameters.get("VisuAcqImagePhaseEncDir")
ds_temp.Columns = int(img_dims[0])
ds_temp.Rows = int(img_dims[1])
if np.size(VisuAcqImagePhaseEncDir) == 1:
ds_temp.InPlanePhaseEncodingDirection = parameters.get("VisuAcqImagePhaseEncDir").split("_")[0]
else:
ds_temp.InPlanePhaseEncodingDirection = parameters.get("VisuAcqImagePhaseEncDir")[0].split("_")[0]
if ds_temp.InPlanePhaseEncodingDirection == "row":
acqmat = np.pad(parameters.get("VisuAcqSize"), 1, "constant")
ds_temp.AcquisitionMatrix = list(np.array(acqmat, dtype=int))
ds_temp.PixelSpacing = [core_ext[0] / img_dims[0], core_ext[1] / img_dims[1]]
pixel_spacing = [core_ext[0] / img_dims[0], core_ext[1] / img_dims[1]]
ds_temp.PixelSpacing = pixel_spacing[::-1]
elif ds_temp.InPlanePhaseEncodingDirection == "col":
acqmat = np.insert(parameters.get("VisuAcqSize"), 1, [0, 0])
ds_temp.AcquisitionMatrix = list(np.flip(np.array(acqmat, dtype=int), 0))
ds_temp.PixelSpacing = [core_ext[1] / img_dims[1], core_ext[0] / img_dims[0]]
gamma = 42.5756
Bo = round(ds_temp.ImagingFrequency / gamma)
ds_temp.MagneticFieldStrength = Bo
elif PV_version == "6.0.1":
########################### ParaVision 6.0.1 ##############################
s = parameters.get("VisuStudyDate")
date = re.sub("\ |\<|\>", "", s)
studydate = dateutil.parser.parse(date)
ds_temp.StudyDate = studydate.strftime("%Y%m%d")
ds_temp.StudyTime = studydate.strftime("%H%M%S")
t = parameters.get("VisuAcqDate")
acqdate = re.sub("\ |\<|\>", "", t)
acquisitiondate = dateutil.parser.parse(acqdate)
ds_temp.AcquisitionDate = acquisitiondate.strftime("%Y%m%d")
ds_temp.AcquisitionTime = acquisitiondate.strftime("%H%M%S")
ds_temp.InPlanePhaseEncodingDirection = parameters.get("VisuAcqGradEncoding")
if ds_temp.InPlanePhaseEncodingDirection[0] == "read_enc":
ds_temp.Columns = int(img_dims[0])
ds_temp.Rows = int(img_dims[1])
acqmat = np.pad(parameters.get("VisuAcqSize"), 1, "constant")
ds_temp.AcquisitionMatrix = list(np.array(acqmat, dtype=int))
ds_temp.PixelSpacing = [core_ext[1] / img_dims[1], core_ext[0] / img_dims[0]]
elif ds_temp.InPlanePhaseEncodingDirection[0] == "phase_enc":
ds_temp.Columns = int(img_dims[1])
ds_temp.Rows = int(img_dims[0])
acqmat = np.insert(parameters.get("VisuAcqSize"), 1, [0, 0])
ds_temp.AcquisitionMatrix = list(np.flip(np.array(acqmat, dtype=int), 0)) # check
ds_temp.PixelSpacing = [core_ext[0] / img_dims[0], core_ext[1] / img_dims[1]]
gamma = 42.5756
Bo = round(ds_temp.ImagingFrequency / gamma)
ds_temp.MagneticFieldStrength = Bo
elif '360' in PV_version:
########################### ParaVision 360 ##############################
VisuStudyDate = parameters.get("VisuStudyDate")
StudyDate=re.sub('\ |\<|\>', '', VisuStudyDate )
StudyDate = dateutil.parser.parse(StudyDate)
ds_temp.StudyDate = StudyDate.strftime("%Y%m%d")
ds_temp.StudyTime = StudyDate.strftime("%H%M%S")
VisuAcqDate = parameters.get("VisuAcqDate")
AcqDate = re.sub('\ |\<|\>', '', VisuAcqDate)
AcqDate = dateutil.parser.parse(AcqDate)
ds_temp.AcquisitionDate = AcqDate.strftime("%Y%m%d")
ds_temp.AcquisitionTime = AcqDate.strftime("%H%M%S")
ds_temp.InPlanePhaseEncodingDirection = parameters.get("VisuAcqGradEncoding")
if ds_temp.InPlanePhaseEncodingDirection[0] == 'read_enc':
ds_temp.Columns = int(img_dims[0])
ds_temp.Rows = int(img_dims[1])
acqmat = np.pad(parameters.get("VisuAcqSize"),1,'constant')
ds_temp.AcquisitionMatrix = list(np.array(acqmat,dtype=int))
ds_temp.PixelSpacing = [core_ext[1]/img_dims[1],core_ext[0]/img_dims[0]]
elif ds_temp.InPlanePhaseEncodingDirection[0] == 'phase_enc':
ds_temp.Columns = int(img_dims[1])
ds_temp.Rows = int(img_dims[0])
acqmat = np.insert(parameters.get("VisuAcqSize"),1,[0,0])
ds_temp.AcquisitionMatrix = list(np.flip(np.array(acqmat,dtype=int),0))
ds_temp.PixelSpacing = ([core_ext[0]/img_dims[0],core_ext[1]/img_dims[1]])
ds_temp.MagneticFieldStrength = parameters.get('VisuMagneticFieldStrength')
# DCE acquisition
if "DCE" in ds_temp.ProtocolName:
NRepetitions = int(method_parameters.get("PVM_NRepetitions"))
enc_matrix = str(method_parameters.get("PVM_EncMatrix"))
enc_step = float(re.findall('[0-9]+',enc_matrix)[1])
total_scan_time = float(ds_temp.RepetitionTime) * NRepetitions * enc_step
scan_time_step = float(ds_temp.RepetitionTime) * enc_step # in ms
vect4 = []
scan_time=0
step = int(nframes/NRepetitions)
for t in range(0,NRepetitions):
scan_time = scan_time + scan_time_step
for kk in range(0,step):
vect4.append(scan_time)
ds_temp.TriggerTime = np.array(vect4)[iteration]
# DWI acquisition
elif "diffusion" in ds_temp.ProtocolName or "EPI" in ds_temp.ProtocolName:
string = str(method_parameters.get("PVM_DwBvalEach"))
b_values = re.findall("[0-9]+", string)
#b_values.pop(0)
b_values.insert(0, "0")
bvalues = []
for elem in b_values:
bvalues.append(float(elem))
vect3 = []
step = int(nframes / len(b_values))
for t in range(0, len(b_values)):
for kk in range(0, step):
vect3.append(bvalues[t])
ds_temp.DiffusionBValue = np.array(vect3)[iteration]
# CEST acquisition
elif "cest" in ds_temp.ProtocolName and method_parameters.get("PVM_SatTransOnOff") == 'On':
ds_temp.Creator = method_parameters.get("OWNER")
ds_temp.ChemicalExchangeSaturationType = method_parameters.get("Method")
ds_temp.SaturationType = method_parameters.get("PVM_SatTransType")
ds_temp.PulseShape = method_parameters.get("PVM_SatTransPulseEnum")
ds_temp.PulseLength = float(method_parameters.get("PVM_SatTransPulse")[0])
ds_temp.B1Saturation = method_parameters.get("PVM_SatTransPulseAmpl_uT")
ds_temp.PulseNumber = int(method_parameters.get("PVM_SatTransNPulses"))
# train module needs to be checked
if 'train' in method_parameters.get("Method"):
tau_p = float(method_parameters.get("PVM_SatTransPulse")[0])
tau_d = float(method_parameters.get("PVM_SatTransInterPulseDelay"))
n = int(method_parameters.get("PVM_SatTransNPulses"))
#method_parameters.get("PVM_SatTransModuleTime") #the result of this two lines should be the same
#magtransmoduletime = (tau_p + tau_d) * n
ds_temp.InterpulseDelay = tau_d
ds_temp.DutyCycle = tau_p/(tau_p + tau_d) * 100
ds_temp.SaturationLength = method_parameters.get("PVM_SatTransModuleTime")
else:
ds_temp.DutyCycle = '100'
ds_temp.SaturationLength = ds_temp.PulseLength * ds_temp.PulseNumber
NSatFreq = method_parameters.get('PVM_NSatFreq')
if NSatFreq != None:
f_step = int(nframes/NSatFreq)
ds_temp.MeasurementNumber = NSatFreq
ds_temp.RecoveryTime = float(ds_temp.RepetitionTime) - float(ds_temp.PulseLength)
freq_list = method_parameters.get('PVM_SatTransFreqValues') # frequency list is formatted differently for CEST Off and On, need to distinguish both cases
freq_list_temp = []
# p = '[-+]?\d*\.\d+|[-+]?\d+'
if re.search('[-+]?\d*\.\d+|[-+]?\d+',freq_list[0]) is not None:
for catch in re.finditer('[-+]?\d*\.\d+|[-+]?\d+', freq_list[0]):
freq_list_temp.append(catch[0])
freq_list = freq_list_temp
if "OFF" not in parameters.get("VisuAcquisitionProtocol") and len(freq_list) > 2:
############## CEST ON ################
if method_parameters.get("PVM_SatTransFreqUnit") == 'unit_ppm':
sat_freq_ppm = np.array(freq_list, dtype=float)
if NSatFreq > 1 and NSatFreq == nframes:
ds_temp.SaturationOffsetPpm = sat_freq_ppm[iteration]
ds_temp.SaturationOffsetHz = sat_freq_ppm[iteration] * ds_temp.ImagingFrequency
elif NSatFreq > 1 and NSatFreq != nframes:
SatFreqPpm = []
for t in range(0, NSatFreq):
for kk in range(0, f_step):
SatFreqPpm.append(sat_freq_ppm[t])
ds_temp.SaturationOffsetPpm = str(np.array(SatFreqPpm,dtype=float)[iteration])
sat_freq_hz = SatFreqPpm[iteration] * ds_temp.ImagingFrequency
ds_temp.SaturationOffsetHz = sat_freq_hz
### Tags for CEST ON only
ds_temp.PulseLength2 = float(method_parameters.get("PVM_SatTransPulseLength2"))
ds_temp.ReadoutTime = (ds_temp.RepetitionTime - ds_temp.PulseLength - (ds_temp.PulseLength2 * (f_step - 1))) / f_step
elif method_parameters.get("PVM_SatTransFreqUnit") == 'unit_hz':
sat_freq_hz = np.array(freq_list, dtype=float)
if NSatFreq > 1 and NSatFreq == nframes:
ds_temp.SaturationOffsetHz = sat_freq_hz[iteration]
ds_temp.SaturationOffsetPpm = sat_freq_hz[iteration] * ds_temp.ImagingFrequency
elif NSatFreq > 1 and NSatFreq != nframes:
SatFreqHz = []
for t in range(0, NSatFreq):
for kk in range(0, f_step):
SatFreqHz.append(sat_freq_hz[t])
ds_temp.SaturationOffsetHz = str(np.array(SatFreqHz,dtype=float)[iteration])
sat_freq_ppm = SatFreqHz[iteration] * ds_temp.ImagingFrequency
ds_temp.SaturationOffsetPpm = sat_freq_ppm
### Tags for CEST ON only
ds_temp.PulseLength2 = float(method_parameters.get("PVM_SatTransPulseLength2"))
ds_temp.ReadoutTime = (ds_temp.RepetitionTime - ds_temp.PulseLength - (ds_temp.PulseLength2 * (f_step - 1))) / f_step
else:
############## CEST OFF ################
if method_parameters.get("PVM_SatTransFreqUnit") == 'unit_ppm':
sat_freq_ppm = np.array(freq_list, dtype=float)
SatFreqPpm = []
for t in range(0, NSatFreq):
for kk in range(0, f_step):
SatFreqPpm.append(sat_freq_ppm[t])
ds_temp.SaturationOffsetPpm = str(np.array(SatFreqPpm,dtype=float)[iteration])
sat_freq_hz = SatFreqPpm[iteration] * ds_temp.ImagingFrequency
ds_temp.SaturationOffsetHz = sat_freq_hz
### Not tested
elif method_parameters.get("PVM_SatTransFreqUnit") == 'unit_hz':
sat_freq_hz = np.array(freq_list, dtype=float)
SatFreqHz= []
for t in range(0, NSatFreq):
for kk in range(0, f_step):
SatFreqHz.append(sat_freq_hz[t])
ds_temp.SaturationOffsetHz = str(np.array(SatFreqHz,dtype=float)[iteration])
sat_freq_ppm = SatFreqHz[iteration] * ds_temp.ImagingFrequency
ds_temp.SaturationOffsetPpm = sat_freq_ppm
elif NSatFreq == None and method_parameters.get("PVM_SatTransFreqUnit") == 'unit_ppm':
freq_list = method_parameters.get('PVM_SatTransFreqValues') # frequency list is formatted differently for CEST Off and On, need to distinguish both cases
freq_list = freq_list[0].split(" ")
while '' in freq_list:
freq_list.remove('')
[elem.strip(' ') for elem in freq_list]
sat_freq_ppm = np.array(freq_list, dtype=float)
ds_temp.SaturationOffsetPpm = sat_freq_ppm[iteration]
ds_temp.SaturationOffsetHz = sat_freq_ppm[iteration] * ds_temp.ImagingFrequency
elif NSatFreq == None and method_parameters.get("PVM_SatTransFreqUnit") == 'unit_hz':
freq_list = method_parameters.get('PVM_SatTransFreqValues') # frequency list is formatted differently for CEST Off and On, need to distinguish both cases
freq_list = freq_list[0].split(" ")
while '' in freq_list:
freq_list.remove('')
[elem.strip(' ') for elem in freq_list]
sat_freq_hz = np.array(freq_list, dtype=float)
ds_temp.SaturationOffsetHz = sat_freq_hz[iteration]
ds_temp.SaturationOffsetPpm = sat_freq_hz[iteration] * ds_temp.ImagingFrequency
# Image pixel module with the tags starting with 0028.
# This group is responsible for describing how to read the pixels
ds_temp.SamplesPerPixel = 1
ds_temp.PhotometricInterpretation = "MONOCHROME2"
ds_temp.PixelRepresentation = 0
ds_temp.BitsAllocated = 16
ds_temp.BitsStored = 16
ds_temp.HighBit = 15
ds_temp.WindowCenterWidthExplanation = "MinMax"
ds_temp.PixelData = layer
ds_temp[0x7FE0, 0x0010].VR = "OW"
ds_temp.WindowWidth = int(np.amax(img) + 1)
ds_temp.WindowCenter = int((np.amax(img) + 1) / 2)
ds_temp[0x0028, 0x1050].VR = "DS"
ds_temp[0x0028, 0x1051].VR = "DS"
ds_temp.SmallestImagePixelValue = int(np.amin(layer))
ds_temp.LargestImagePixelValue = int(np.amax(layer))
ds_temp[0x0028, 0x0106].VR = "US"
ds_temp[0x0028, 0x0107].VR = "US"
ds_temp.RescaleSlope = factor
for j in range(0, nframes - 1):
ds_temp.RescaleIntercept = str(parameters.get("VisuCoreDataOffs")[j])
# Set creation date/time
dt = datetime.datetime.now()
ds_temp.InstanceCreationDate = dt.strftime("%Y%m%d")
timeStr = dt.strftime("%H%M%S")
ds_temp.InstanceCreationTime = timeStr
ds_temp.NumberOfSlices = acqp_parameters.get("NSLICES")
string2 = str(reco_parameters.get("RECO_fov"))
vect2 = re.findall("[0-9]+", string2)
vect2.pop(0)
vect3 = []
for elem in vect2:
vect3.append(float(elem))
ds_temp.ReconstructionFieldOfView = vect3
outfile = "%s%s.dcm" % (filename_little_endian, str(iteration + 1))
# Save DICOM files in separate slices
os.chdir(dst_path)
ds_temp.is_little_endian = True
ds_temp.is_implicit_VR = False
ds_temp.save_as(outfile)
print(str(dirs[0].split('/')[-1]) + ' done!')