def __validateSizeAndDimension(self, *args):
names = []
dims = []
sizes = []
for source in args:
if source:
names.append(source)
dimensions = mriutil.getMriDimensions(source)
if len(dimensions) == 4:
dims.append([dimensions[0], dimensions[1], dimensions[2]])
else:
dims.append(dimensions)
# sourceSize sanitization
sourceSize = mriutil.getMriVoxelSize(source)
try:
sourceSize = [
"{:.1f}".format(float(val)) for val in sourceSize
]
except ValueError:
self.error("Error during sourceSize sanitization")
sizes.append(sourceSize)
if not dims[1:] == dims[:-1]:
self.error(
"Dimension for each scale mismatch found between images: {}".
format(", ".join(names)))
if not sizes[1:] == sizes[:-1]:
self.error("Voxel size mismatch found between images: {}".format(
", ".join(names)))
def implement(self):
dwi = self.__linkDwiImage()
bVals= self.getCorrectionImage('grad', None, 'bvals')
bVecs= self.getCorrectionImage('grad', None, 'bvecs')
bEnc = self.getCorrectionImage('grad', None, 'benc')
if not bVals or not bVecs:
bVals= self.getPreparationImage('grad', None, 'bvals')
bVecs= self.getPreparationImage('grad', None, 'bvecs')
bEnc= self.getPreparationImage('grad', None, 'benc')
bVals = util.symlink(bVals, self.workingDir)
bVecs = util.symlink(bVecs, self.workingDir)
bEnc = util.symlink(bEnc, self.workingDir)
if self.get('skipUpsampling'):
dwiUpsample = self.rename(os.path.join(self.workingDir, os.path.basename(dwi)), self.buildName(dwi, "upsample"))
else:
interp = self.get('interp')
template = self.getParcellationImage('anat','freesurfer','nii.gz')
voxelSize = mriutil.getMriVoxelSize(template) # Get t1 voxel size to upsample
voxelSize = str(voxelSize).translate(None, '[],') # Remove specific caracteres
dwiUpsample= self.__upsampling(dwi, voxelSize, interp, self.buildName(dwi, "upsample"))
b0Upsample = os.path.join(self.workingDir, os.path.basename(dwiUpsample).replace(self.get("prefix", 'dwi'), self.get("prefix", 'b0')))
self.info(mriutil.extractFirstB0FromDwi(dwiUpsample, b0Upsample, bVals))
def __validateSizeAndDimension(self, *args):
names = []
dims = []
sizes = []
for source in args:
if source:
names.append(source)
dimensions = mriutil.getMriDimensions(source)
if len(dimensions) == 4:
dims.append([dimensions[0], dimensions[1], dimensions[2]])
else:
dims.append(dimensions)
# sourceSize sanitization
sourceSize = mriutil.getMriVoxelSize(source)
try:
sourceSize = ["{:.1f}".format(float(val)) for val in sourceSize]
except ValueError:
self.error("Error during sourceSize sanitization")
sizes.append(sourceSize)
if not dims[1:] == dims[:-1]:
self.error("Dimension for each scale mismatch found between images: {}".format(", ".join(names)))
if not sizes[1:] == sizes[:-1]:
self.error("Voxel size mismatch found between images: {}".format(", ".join(names)))
def __validateSizeAndDimension(self, dwi, b0PA, b0AP):
dwiDim = mriutil.getMriDimensions(dwi)
dwiVoxel = mriutil.getMriVoxelSize(dwi)
b0PADim = mriutil.getMriDimensions(b0PA)
b0PAVoxel = mriutil.getMriVoxelSize(b0PA)
b0APDim = mriutil.getMriDimensions(b0AP)
b0APVoxel = mriutil.getMriVoxelSize(b0AP)
self.info("Look if {} and {} and {} have the same voxel size".format(dwi, b0PA, b0AP))
if len(dwiVoxel) == len(b0PAVoxel) == len(b0APVoxel) == 3:
for i in range(0,len(dwiVoxel)):
if not (dwiVoxel[i] == b0PAVoxel[i] == b0APVoxel[i]):
self.error("Voxel size mismatch found at index {} for image {} {} {}".format(i, dwi, b0PA, b0AP))
else:
self.error("Found Voxel size inconsistency for image {} or {} or {}".format(dwi, b0PA, b0AP))
self.info("Look if {} and {} and {} have the same dimension for each scale".format(dwi, b0PA, b0AP))
for i in range(0,3):
if not (dwiDim[i]==b0PADim[i]==b0APDim[i]):
self.error("Dimensions mismatch found at index {} for image {} {} {}".format(i, dwi, b0PA, b0AP))
def implement(self):
#Noise mask computation
brainMask = self.getCorrectionImage('mask', 'corrected')
noiseMask = self.__computeNoiseMask(brainMask)
#Voxel Size of native dwi
dwiNative = self.getPreparationImage('dwi')
voxelSize = mriutil.getMriVoxelSize(dwiNative)
#Corpus Callosum masks
ccMask = self.getMaskingImage('aparc_aseg', ['253','mask'])
ccMaskDownsample = self.buildName(ccMask, 'downsample')
cmdString = "mri_convert -voxsize {} -rl {} --input_volume {} --output_volume {}"
cmd = cmdString.format(" ".join(voxelSize), brainMask, ccMask, ccMaskDownsample)
self.launchCommand(cmd)
def implement(self):
# Noise mask computation
brainMask = self.getCorrectionImage("mask", "corrected")
noiseMask = mriutil.computeNoiseMask(brainMask, self.buildName(brainMask, "noisemask"))
# Voxel Size of native dwi
dwiNative = self.getPreparationImage("dwi")
voxelSize = mriutil.getMriVoxelSize(dwiNative)
# Corpus Callosum masks
ccMask = self.getMaskingImage("aparc_aseg", ["253", "mask"])
ccMaskDownsample = self.buildName(ccMask, "downsample")
cmdString = "mri_convert -voxsize {} -rl {} --input_volume {} --output_volume {}"
cmd = cmdString.format(" ".join(voxelSize), brainMask, ccMask, ccMaskDownsample)
self.launchCommand(cmd)
def implement(self):
#Noise mask computation
brainMask = self.getCorrectionImage('mask', 'corrected')
noiseMask = mriutil.computeNoiseMask(
brainMask, self.buildName(brainMask, 'noisemask'))
#Voxel Size of native dwi
dwiNative = self.getPreparationImage('dwi')
voxelSize = mriutil.getMriVoxelSize(dwiNative)
#Corpus Callosum masks
ccMask = self.getMaskingImage('aparc_aseg', ['253', 'mask'])
ccMaskDownsample = self.buildName(ccMask, 'downsample')
cmdString = "mri_convert -voxsize {} -rl {} --input_volume {} --output_volume {}"
cmd = cmdString.format(" ".join(voxelSize), brainMask, ccMask,
ccMaskDownsample)
self.launchCommand(cmd)
def __validateSizeAndDimension(self, *args):
names = []
dims = []
sizes = []
for source in args:
if source:
names.append(source)
dimensions = mriutil.getMriDimensions(source)
if len(dimensions) == 4:
dims.append([dimensions[0], dimensions[1], dimensions[2]])
else:
dims.append(dimensions)
sizes.append(mriutil.getMriVoxelSize(source))
if not dims[1:] == dims[:-1]:
self.error("Dimension for each scale mismatch found between images: {}".format(", ".join(names)))
if not sizes[1:] == sizes[:-1]:
self.error("Voxel size mismatch found between images: {}".format(", ".join(names)))