def get_data_or_scalar(argument, data_in):
"""
Get data from list of file names (scenario 1) or scalar (scenario 2)
:param argument: list of file names of scalar
:param data_in: if argument is scalar, use data to get shape
:return: 3d or 4d numpy array
"""
if argument.replace('.', '').isdigit(): # so that it recognize float as digits too
# build data2 with same shape as data
data_out = data_in[:, :, :] * 0 + float(argument)
else:
# parse file name and check integrity
parser2 = Parser(__file__)
parser2.add_option(name='-i', type_value=[[','], 'file'])
list_fname = parser2.parse(['-i', argument]).get('-i')
data_out = get_data(list_fname)
return data_out
def get_data_or_scalar(argument, data_in):
"""
Get data from list of file names (scenario 1) or scalar (scenario 2)
:param argument: list of file names of scalar
:param data_in: if argument is scalar, use data to get np.shape
:return: 3d or 4d numpy array
"""
# try to convert argument in float
try:
# build data2 with same shape as data
data_out = data_in[:, :, :] * 0 + float(argument)
# if conversion fails, it should be a file
except:
# parse file name and check integrity
parser2 = Parser(__file__)
parser2.add_option(name='-i', type_value=[[','], 'file'])
list_fname = parser2.parse(['-i', argument]).get('-i')
data_out = get_data(list_fname)
return data_out
def get_data_or_scalar(argument, data_in):
"""
Get data from list of file names (scenario 1) or scalar (scenario 2)
:param argument: list of file names of scalar
:param data_in: if argument is scalar, use data to get np.shape
:return: 3d or 4d numpy array
"""
# try to convert argument in float
try:
# build data2 with same shape as data
data_out = data_in[:, :, :] * 0 + float(argument)
# if conversion fails, it should be a file
except:
# parse file name and check integrity
parser2 = Parser(__file__)
parser2.add_option(name='-i', type_value=[[','], 'file'])
list_fname = parser2.parse(['-i', argument]).get('-i')
data_out = get_data(list_fname)
return data_out
description="reference volume for label removing.",
mandatory=False)
parser.add_option(name="-c",
type_value="int",
description="cross radius in mm (default=5mm).",
mandatory=False)
parser.add_option(name="-d",
type_value=None,
description="dilatation bool for cross generation ('-c' option).",
mandatory=False)
parser.add_option(name="-v",
type_value="multiple_choice",
description="verbose. Default=" + str(param_default.verbose),
mandatory=False,
example=['0', '1'])
arguments = parser.parse(sys.argv[1:])
input_filename = arguments["-i"]
process_type = arguments["-t"]
input_fname_output = None
input_fname_ref = None
input_cross_radius = 5
input_dilate = False
input_coordinates = None
input_verbose = '1'
input_fname_output = arguments["-o"]
if "-r" in arguments:
input_fname_ref = arguments["-r"]
if "-x" in arguments:
input_coordinates = arguments["-x"]
if "-c" in arguments:
def main():
# get default parameters
step1 = Paramreg(step='1', type='seg', algo='slicereg', metric='MeanSquares', iter='10')
step2 = Paramreg(step='2', type='im', algo='syn', metric='MI', iter='3')
# step1 = Paramreg()
paramreg = ParamregMultiStep([step1, step2])
# step1 = Paramreg_step(step='1', type='seg', algo='bsplinesyn', metric='MeanSquares', iter='10', shrink='1', smooth='0', gradStep='0.5')
# step2 = Paramreg_step(step='2', type='im', algo='syn', metric='MI', iter='10', shrink='1', smooth='0', gradStep='0.5')
# paramreg = ParamregMultiStep([step1, step2])
# Initialize the parser
parser = Parser(__file__)
parser.usage.set_description('Register anatomical image to the template.')
parser.add_option(name="-i",
type_value="file",
description="Anatomical image.",
mandatory=True,
example="anat.nii.gz")
parser.add_option(name="-s",
type_value="file",
description="Spinal cord segmentation.",
mandatory=True,
example="anat_seg.nii.gz")
parser.add_option(name="-l",
type_value="file",
description="Labels. See: http://sourceforge.net/p/spinalcordtoolbox/wiki/create_labels/",
mandatory=True,
default_value='',
example="anat_labels.nii.gz")
parser.add_option(name="-t",
type_value="folder",
description="Path to MNI-Poly-AMU template.",
mandatory=False,
default_value=param.path_template)
parser.add_option(name="-p",
type_value=[[':'], 'str'],
description="""Parameters for registration (see sct_register_multimodal). Default:\n--\nstep=1\ntype="""+paramreg.steps['1'].type+"""\nalgo="""+paramreg.steps['1'].algo+"""\nmetric="""+paramreg.steps['1'].metric+"""\npoly="""+paramreg.steps['1'].poly+"""\n--\nstep=2\ntype="""+paramreg.steps['2'].type+"""\nalgo="""+paramreg.steps['2'].algo+"""\nmetric="""+paramreg.steps['2'].metric+"""\niter="""+paramreg.steps['2'].iter+"""\nshrink="""+paramreg.steps['2'].shrink+"""\nsmooth="""+paramreg.steps['2'].smooth+"""\ngradStep="""+paramreg.steps['2'].gradStep+"""\n--""",
mandatory=False,
example="step=2,type=seg,algo=bsplinesyn,metric=MeanSquares,iter=5,shrink=2:step=3,type=im,algo=syn,metric=MI,iter=5,shrink=1,gradStep=0.3")
parser.add_option(name="-r",
type_value="multiple_choice",
description="""Remove temporary files.""",
mandatory=False,
default_value='1',
example=['0', '1'])
parser.add_option(name="-v",
type_value="multiple_choice",
description="""Verbose. 0: nothing. 1: basic. 2: extended.""",
mandatory=False,
default_value=param.verbose,
example=['0', '1', '2'])
if param.debug:
print '\n*** WARNING: DEBUG MODE ON ***\n'
fname_data = '/Users/julien/data/temp/sct_example_data/t2/t2.nii.gz'
fname_landmarks = '/Users/julien/data/temp/sct_example_data/t2/labels.nii.gz'
fname_seg = '/Users/julien/data/temp/sct_example_data/t2/t2_seg.nii.gz'
path_template = param.path_template
remove_temp_files = 0
verbose = 2
# speed = 'superfast'
#param_reg = '2,BSplineSyN,0.6,MeanSquares'
else:
arguments = parser.parse(sys.argv[1:])
# get arguments
fname_data = arguments['-i']
fname_seg = arguments['-s']
fname_landmarks = arguments['-l']
path_template = arguments['-t']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
if '-p' in arguments:
paramreg_user = arguments['-p']
# update registration parameters
for paramStep in paramreg_user:
paramreg.addStep(paramStep)
# initialize other parameters
file_template = param.file_template
file_template_label = param.file_template_label
file_template_seg = param.file_template_seg
output_type = param.output_type
zsubsample = param.zsubsample
# smoothing_sigma = param.smoothing_sigma
# start timer
start_time = time.time()
# get absolute path - TO DO: remove! NEVER USE ABSOLUTE PATH...
path_template = os.path.abspath(path_template)
# get fname of the template + template objects
fname_template = sct.slash_at_the_end(path_template, 1)+file_template
fname_template_label = sct.slash_at_the_end(path_template, 1)+file_template_label
fname_template_seg = sct.slash_at_the_end(path_template, 1)+file_template_seg
# check file existence
sct.printv('\nCheck template files...')
sct.check_file_exist(fname_template, verbose)
sct.check_file_exist(fname_template_label, verbose)
sct.check_file_exist(fname_template_seg, verbose)
# print arguments
sct.printv('\nCheck parameters:', verbose)
sct.printv('.. Data: '+fname_data, verbose)
sct.printv('.. Landmarks: '+fname_landmarks, verbose)
sct.printv('.. Segmentation: '+fname_seg, verbose)
sct.printv('.. Path template: '+path_template, verbose)
sct.printv('.. Output type: '+str(output_type), verbose)
sct.printv('.. Remove temp files: '+str(remove_temp_files), verbose)
sct.printv('\nParameters for registration:')
for pStep in range(1, len(paramreg.steps)+1):
sct.printv('Step #'+paramreg.steps[str(pStep)].step, verbose)
sct.printv('.. Type #'+paramreg.steps[str(pStep)].type, verbose)
sct.printv('.. Algorithm................ '+paramreg.steps[str(pStep)].algo, verbose)
sct.printv('.. Metric................... '+paramreg.steps[str(pStep)].metric, verbose)
sct.printv('.. Number of iterations..... '+paramreg.steps[str(pStep)].iter, verbose)
sct.printv('.. Shrink factor............ '+paramreg.steps[str(pStep)].shrink, verbose)
sct.printv('.. Smoothing factor......... '+paramreg.steps[str(pStep)].smooth, verbose)
sct.printv('.. Gradient step............ '+paramreg.steps[str(pStep)].gradStep, verbose)
sct.printv('.. Degree of polynomial..... '+paramreg.steps[str(pStep)].poly, verbose)
path_data, file_data, ext_data = sct.extract_fname(fname_data)
sct.printv('\nCheck input labels...')
# check if label image contains coherent labels
image_label = Image(fname_landmarks)
# -> all labels must be different
labels = image_label.getNonZeroCoordinates(sorting='value')
hasDifferentLabels = True
for lab in labels:
for otherlabel in labels:
if lab != otherlabel and lab.hasEqualValue(otherlabel):
hasDifferentLabels = False
break
if not hasDifferentLabels:
sct.printv('ERROR: Wrong landmarks input. All labels must be different.', verbose, 'error')
# all labels must be available in tempalte
image_label_template = Image(fname_template_label)
labels_template = image_label_template.getNonZeroCoordinates(sorting='value')
if labels[-1].value > labels_template[-1].value:
sct.printv('ERROR: Wrong landmarks input. Labels must have correspondance in tempalte space. \nLabel max '
'provided: ' + str(labels[-1].value) + '\nLabel max from template: ' +
str(labels_template[-1].value), verbose, 'error')
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = 'tmp.'+time.strftime("%y%m%d%H%M%S")
status, output = sct.run('mkdir '+path_tmp)
# copy files to temporary folder
sct.printv('\nCopy files...', verbose)
sct.run('isct_c3d '+fname_data+' -o '+path_tmp+'/data.nii')
sct.run('isct_c3d '+fname_landmarks+' -o '+path_tmp+'/landmarks.nii.gz')
sct.run('isct_c3d '+fname_seg+' -o '+path_tmp+'/segmentation.nii.gz')
sct.run('isct_c3d '+fname_template+' -o '+path_tmp+'/template.nii')
sct.run('isct_c3d '+fname_template_label+' -o '+path_tmp+'/template_labels.nii.gz')
sct.run('isct_c3d '+fname_template_seg+' -o '+path_tmp+'/template_seg.nii.gz')
# go to tmp folder
os.chdir(path_tmp)
# resample data to 1mm isotropic
sct.printv('\nResample data to 1mm isotropic...', verbose)
sct.run('isct_c3d data.nii -resample-mm 1.0x1.0x1.0mm -interpolation Linear -o datar.nii')
sct.run('isct_c3d segmentation.nii.gz -resample-mm 1.0x1.0x1.0mm -interpolation NearestNeighbor -o segmentationr.nii.gz')
# N.B. resampling of labels is more complicated, because they are single-point labels, therefore resampling with neighrest neighbour can make them disappear. Therefore a more clever approach is required.
resample_labels('landmarks.nii.gz', 'datar.nii', 'landmarksr.nii.gz')
# # TODO
# sct.run('sct_label_utils -i datar.nii -t create -x 124,186,19,2:129,98,23,8 -o landmarksr.nii.gz')
# Change orientation of input images to RPI
sct.printv('\nChange orientation of input images to RPI...', verbose)
set_orientation('datar.nii', 'RPI', 'data_rpi.nii')
set_orientation('landmarksr.nii.gz', 'RPI', 'landmarks_rpi.nii.gz')
set_orientation('segmentationr.nii.gz', 'RPI', 'segmentation_rpi.nii.gz')
# # Change orientation of input images to RPI
# sct.printv('\nChange orientation of input images to RPI...', verbose)
# set_orientation('data.nii', 'RPI', 'data_rpi.nii')
# set_orientation('landmarks.nii.gz', 'RPI', 'landmarks_rpi.nii.gz')
# set_orientation('segmentation.nii.gz', 'RPI', 'segmentation_rpi.nii.gz')
# get landmarks in native space
# crop segmentation
# output: segmentation_rpi_crop.nii.gz
sct.run('sct_crop_image -i segmentation_rpi.nii.gz -o segmentation_rpi_crop.nii.gz -dim 2 -bzmax')
# straighten segmentation
sct.printv('\nStraighten the spinal cord using centerline/segmentation...', verbose)
sct.run('sct_straighten_spinalcord -i segmentation_rpi_crop.nii.gz -c segmentation_rpi_crop.nii.gz -r 0 -v '+str(verbose), verbose)
# re-define warping field using non-cropped space (to avoid issue #367)
sct.run('sct_concat_transfo -w warp_straight2curve.nii.gz -d data_rpi.nii -o warp_straight2curve.nii.gz')
# Label preparation:
# --------------------------------------------------------------------------------
# Remove unused label on template. Keep only label present in the input label image
sct.printv('\nRemove unused label on template. Keep only label present in the input label image...', verbose)
sct.run('sct_label_utils -t remove -i template_labels.nii.gz -o template_label.nii.gz -r landmarks_rpi.nii.gz')
# Make sure landmarks are INT
sct.printv('\nConvert landmarks to INT...', verbose)
sct.run('isct_c3d template_label.nii.gz -type int -o template_label.nii.gz', verbose)
# Create a cross for the template labels - 5 mm
sct.printv('\nCreate a 5 mm cross for the template labels...', verbose)
sct.run('sct_label_utils -t cross -i template_label.nii.gz -o template_label_cross.nii.gz -c 5')
# Create a cross for the input labels and dilate for straightening preparation - 5 mm
sct.printv('\nCreate a 5mm cross for the input labels and dilate for straightening preparation...', verbose)
sct.run('sct_label_utils -t cross -i landmarks_rpi.nii.gz -o landmarks_rpi_cross3x3.nii.gz -c 5 -d')
# Apply straightening to labels
sct.printv('\nApply straightening to labels...', verbose)
sct.run('sct_apply_transfo -i landmarks_rpi_cross3x3.nii.gz -o landmarks_rpi_cross3x3_straight.nii.gz -d segmentation_rpi_crop_straight.nii.gz -w warp_curve2straight.nii.gz -x nn')
# Convert landmarks from FLOAT32 to INT
sct.printv('\nConvert landmarks from FLOAT32 to INT...', verbose)
sct.run('isct_c3d landmarks_rpi_cross3x3_straight.nii.gz -type int -o landmarks_rpi_cross3x3_straight.nii.gz')
# Remove labels that do not correspond with each others.
sct.printv('\nRemove labels that do not correspond with each others.', verbose)
sct.run('sct_label_utils -t remove-symm -i landmarks_rpi_cross3x3_straight.nii.gz -o landmarks_rpi_cross3x3_straight.nii.gz,template_label_cross.nii.gz -r template_label_cross.nii.gz')
# Estimate affine transfo: straight --> template (landmark-based)'
sct.printv('\nEstimate affine transfo: straight anat --> template (landmark-based)...', verbose)
# converting landmarks straight and curved to physical coordinates
image_straight = Image('landmarks_rpi_cross3x3_straight.nii.gz')
landmark_straight = image_straight.getNonZeroCoordinates(sorting='value')
image_template = Image('template_label_cross.nii.gz')
landmark_template = image_template.getNonZeroCoordinates(sorting='value')
# Reorganize landmarks
points_fixed, points_moving = [], []
landmark_straight_mean = []
for coord in landmark_straight:
if coord.value not in [c.value for c in landmark_straight_mean]:
temp_landmark = coord
temp_number = 1
for other_coord in landmark_straight:
if coord.hasEqualValue(other_coord) and coord != other_coord:
temp_landmark += other_coord
temp_number += 1
landmark_straight_mean.append(temp_landmark / temp_number)
for coord in landmark_straight_mean:
point_straight = image_straight.transfo_pix2phys([[coord.x, coord.y, coord.z]])
points_moving.append([point_straight[0][0], point_straight[0][1], point_straight[0][2]])
for coord in landmark_template:
point_template = image_template.transfo_pix2phys([[coord.x, coord.y, coord.z]])
points_fixed.append([point_template[0][0], point_template[0][1], point_template[0][2]])
# Register curved landmarks on straight landmarks based on python implementation
sct.printv('\nComputing rigid transformation (algo=translation-scaling-z) ...', verbose)
import msct_register_landmarks
(rotation_matrix, translation_array, points_moving_reg, points_moving_barycenter) = \
msct_register_landmarks.getRigidTransformFromLandmarks(
points_fixed, points_moving, constraints='translation-scaling-z', show=False)
# writing rigid transformation file
text_file = open("straight2templateAffine.txt", "w")
text_file.write("#Insight Transform File V1.0\n")
text_file.write("#Transform 0\n")
text_file.write("Transform: FixedCenterOfRotationAffineTransform_double_3_3\n")
text_file.write("Parameters: %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f\n" % (
1.0/rotation_matrix[0, 0], rotation_matrix[0, 1], rotation_matrix[0, 2],
rotation_matrix[1, 0], 1.0/rotation_matrix[1, 1], rotation_matrix[1, 2],
rotation_matrix[2, 0], rotation_matrix[2, 1], 1.0/rotation_matrix[2, 2],
translation_array[0, 0], translation_array[0, 1], -translation_array[0, 2]))
text_file.write("FixedParameters: %.9f %.9f %.9f\n" % (points_moving_barycenter[0],
points_moving_barycenter[1],
points_moving_barycenter[2]))
text_file.close()
# Apply affine transformation: straight --> template
sct.printv('\nApply affine transformation: straight --> template...', verbose)
sct.run('sct_concat_transfo -w warp_curve2straight.nii.gz,straight2templateAffine.txt -d template.nii -o warp_curve2straightAffine.nii.gz')
sct.run('sct_apply_transfo -i data_rpi.nii -o data_rpi_straight2templateAffine.nii -d template.nii -w warp_curve2straightAffine.nii.gz')
sct.run('sct_apply_transfo -i segmentation_rpi.nii.gz -o segmentation_rpi_straight2templateAffine.nii.gz -d template.nii -w warp_curve2straightAffine.nii.gz -x linear')
# threshold to 0.5
nii = Image('segmentation_rpi_straight2templateAffine.nii.gz')
data = nii.data
data[data < 0.5] = 0
nii.data = data
nii.setFileName('segmentation_rpi_straight2templateAffine_th.nii.gz')
nii.save()
# find min-max of anat2template (for subsequent cropping)
zmin_template, zmax_template = find_zmin_zmax('segmentation_rpi_straight2templateAffine_th.nii.gz')
# crop template in z-direction (for faster processing)
sct.printv('\nCrop data in template space (for faster processing)...', verbose)
sct.run('sct_crop_image -i template.nii -o template_crop.nii -dim 2 -start '+str(zmin_template)+' -end '+str(zmax_template))
sct.run('sct_crop_image -i template_seg.nii.gz -o template_seg_crop.nii.gz -dim 2 -start '+str(zmin_template)+' -end '+str(zmax_template))
sct.run('sct_crop_image -i data_rpi_straight2templateAffine.nii -o data_rpi_straight2templateAffine_crop.nii -dim 2 -start '+str(zmin_template)+' -end '+str(zmax_template))
sct.run('sct_crop_image -i segmentation_rpi_straight2templateAffine.nii.gz -o segmentation_rpi_straight2templateAffine_crop.nii.gz -dim 2 -start '+str(zmin_template)+' -end '+str(zmax_template))
# sub-sample in z-direction
sct.printv('\nSub-sample in z-direction (for faster processing)...', verbose)
sct.run('sct_resample -i template_crop.nii -o template_crop_r.nii -f 1x1x'+zsubsample, verbose)
sct.run('sct_resample -i template_seg_crop.nii.gz -o template_seg_crop_r.nii.gz -f 1x1x'+zsubsample, verbose)
sct.run('sct_resample -i data_rpi_straight2templateAffine_crop.nii -o data_rpi_straight2templateAffine_crop_r.nii -f 1x1x'+zsubsample, verbose)
sct.run('sct_resample -i segmentation_rpi_straight2templateAffine_crop.nii.gz -o segmentation_rpi_straight2templateAffine_crop_r.nii.gz -f 1x1x'+zsubsample, verbose)
# Registration straight spinal cord to template
sct.printv('\nRegister straight spinal cord to template...', verbose)
# loop across registration steps
warp_forward = []
warp_inverse = []
for i_step in range(1, len(paramreg.steps)+1):
sct.printv('\nEstimate transformation for step #'+str(i_step)+'...', verbose)
# identify which is the src and dest
if paramreg.steps[str(i_step)].type == 'im':
src = 'data_rpi_straight2templateAffine_crop_r.nii'
dest = 'template_crop_r.nii'
interp_step = 'linear'
elif paramreg.steps[str(i_step)].type == 'seg':
src = 'segmentation_rpi_straight2templateAffine_crop_r.nii.gz'
dest = 'template_seg_crop_r.nii.gz'
interp_step = 'nn'
else:
sct.printv('ERROR: Wrong image type.', 1, 'error')
# if step>1, apply warp_forward_concat to the src image to be used
if i_step > 1:
# sct.run('sct_apply_transfo -i '+src+' -d '+dest+' -w '+','.join(warp_forward)+' -o '+sct.add_suffix(src, '_reg')+' -x '+interp_step, verbose)
sct.run('sct_apply_transfo -i '+src+' -d '+dest+' -w '+','.join(warp_forward)+' -o '+sct.add_suffix(src, '_reg')+' -x '+interp_step, verbose)
src = sct.add_suffix(src, '_reg')
# register src --> dest
warp_forward_out, warp_inverse_out = register(src, dest, paramreg, param, str(i_step))
warp_forward.append(warp_forward_out)
warp_inverse.append(warp_inverse_out)
# Concatenate transformations:
sct.printv('\nConcatenate transformations: anat --> template...', verbose)
sct.run('sct_concat_transfo -w warp_curve2straightAffine.nii.gz,'+','.join(warp_forward)+' -d template.nii -o warp_anat2template.nii.gz', verbose)
# sct.run('sct_concat_transfo -w warp_curve2straight.nii.gz,straight2templateAffine.txt,'+','.join(warp_forward)+' -d template.nii -o warp_anat2template.nii.gz', verbose)
warp_inverse.reverse()
sct.run('sct_concat_transfo -w '+','.join(warp_inverse)+',-straight2templateAffine.txt,warp_straight2curve.nii.gz -d data.nii -o warp_template2anat.nii.gz', verbose)
# Apply warping fields to anat and template
if output_type == 1:
sct.run('sct_apply_transfo -i template.nii -o template2anat.nii.gz -d data.nii -w warp_template2anat.nii.gz -c 1', verbose)
sct.run('sct_apply_transfo -i data.nii -o anat2template.nii.gz -d template.nii -w warp_anat2template.nii.gz -c 1', verbose)
# come back to parent folder
os.chdir('..')
# Generate output files
sct.printv('\nGenerate output files...', verbose)
sct.generate_output_file(path_tmp+'/warp_template2anat.nii.gz', 'warp_template2anat.nii.gz', verbose)
sct.generate_output_file(path_tmp+'/warp_anat2template.nii.gz', 'warp_anat2template.nii.gz', verbose)
if output_type == 1:
sct.generate_output_file(path_tmp+'/template2anat.nii.gz', 'template2anat'+ext_data, verbose)
sct.generate_output_file(path_tmp+'/anat2template.nii.gz', 'anat2template'+ext_data, verbose)
# Delete temporary files
if remove_temp_files:
sct.printv('\nDelete temporary files...', verbose)
sct.run('rm -rf '+path_tmp)
# display elapsed time
elapsed_time = time.time() - start_time
sct.printv('\nFinished! Elapsed time: '+str(int(round(elapsed_time)))+'s', verbose)
# to view results
sct.printv('\nTo view results, type:', verbose)
sct.printv('fslview '+fname_data+' template2anat -b 0,4000 &', verbose, 'info')
sct.printv('fslview '+fname_template+' -b 0,5000 anat2template &\n', verbose, 'info')
# Start program
#=======================================================================================================================
if __name__ == "__main__":
# initialize parameters
param = param()
# call main function
# Initialize the parser
parser = Parser(__file__)
parser.usage.set_description('Utility function for labels.')
parser.add_option(name="-i",
type_value="file",
description="Image to invert.",
mandatory=True,
example="my_image.nii.gz")
parser.add_option(name="-o",
type_value="file_output",
description="output image.",
mandatory=False,
example="output_image.nii.gz",
default_value="inverted_image.nii.gz")
arguments = parser.parse(sys.argv[1:])
input_filename = arguments["-i"]
image_input = Image(input_filename)
image_output = image_input.invert()
if "-o" in arguments:
image_output.setFileName(arguments["-o"])
image_output.save(type='minimize')
def main():
# Initialization
fname_output = ''
fname_mask = param.fname_mask
fname_src_seg = ''
fsloutput = 'export FSLOUTPUTTYPE=NIFTI; ' # for faster processing, all outputs are in NIFTI'
start_time = time.time()
# get path of the toolbox
status, path_sct = commands.getstatusoutput('echo $SCT_DIR')
# get default registration parameters
# step1 = Paramreg(step='1', type='im', algo='syn', metric='MI', iter='5', shrink='1', smooth='0', gradStep='0.5')
step0 = Paramreg(step='0',
type='im',
algo='syn',
metric='MI',
iter='0',
shrink='1',
smooth='0',
gradStep='0.5') # only used to put src into dest space
step1 = Paramreg()
paramreg = ParamregMultiStep([step0, step1])
# Initialize the parser
parser = Parser(__file__)
parser.usage.set_description(
'This program co-registers two 3D volumes. The deformation is non-rigid and is '
'constrained along Z direction (i.e., axial plane). Hence, this function assumes '
'that orientation of the destination image is axial (RPI). If you need to register '
'two volumes with large deformations and/or different contrasts, it is recommended to '
'input spinal cord segmentations (binary mask) in order to achieve maximum robustness.'
' The program outputs a warping field that can be used to register other images to the'
' destination image. To apply the warping field to another image, use '
'sct_apply_transfo')
parser.add_option(name="-i",
type_value="file",
description="Image source.",
mandatory=True,
example="src.nii.gz")
parser.add_option(name="-d",
type_value="file",
description="Image destination.",
mandatory=True,
example="dest.nii.gz")
parser.add_option(name="-iseg",
type_value="file",
description="Segmentation source.",
mandatory=False,
example="src_seg.nii.gz")
parser.add_option(name="-dseg",
type_value="file",
description="Segmentation destination.",
mandatory=False,
example="dest_seg.nii.gz")
parser.add_option(
name="-m",
type_value="file",
description=
"Mask that can be created with sct_create_mask to improve accuracy over region of interest. "
"This mask will be used on the destination image.",
mandatory=False,
example="mask.nii.gz")
parser.add_option(name="-o",
type_value="file_output",
description="Name of output file.",
mandatory=False,
example="src_reg.nii.gz")
parser.add_option(
name="-p",
type_value=[[':'], 'str'],
description=
"""Parameters for registration. Separate arguments with ",". Separate steps with ":".\nstep: <int> Step number (starts at 1).\ntype: {im,seg} type of data used for registration.\nalgo: Default="""
+ paramreg.steps['1'].algo +
"""\n global registration: {rigid, affine, syn, bsplinesyn}\n Slice By Slice registration: {slicereg: regularized translations (see: goo.gl/Sj3ZeU), slicereg2d_translation: regularized using moving average (Hanning window), slicereg2d_rigid, slicereg2d_affine, slicereg2d_pointwise: registration based on the Center of Mass of each slice (use only with type:Seg. Designed for centerlines), slicereg2d_bsplinesyn, slicereg2d_syn}\nmetric: {CC,MI,MeanSquares}. Default="""
+ paramreg.steps['1'].metric +
"""\niter: <int> Number of iterations. Default=""" +
paramreg.steps['1'].iter +
"""\nshrink: <int> Shrink factor (only for SyN). Default=""" +
paramreg.steps['1'].shrink +
"""\nsmooth: <int> Smooth factor (only for SyN). Default=""" +
paramreg.steps['1'].smooth +
"""\ngradStep: <float> Gradient step. Default=""" +
paramreg.steps['1'].gradStep +
"""\npoly: <int> Polynomial degree (only for slicereg). Default=""" +
paramreg.steps['1'].poly +
"""\nwindow_length: <int> size of hanning window for smoothing along z for slicereg2d_pointwise, slicereg2d_translation, slicereg2d_rigid, slicereg2d_affine, slicereg2d_syn and slicereg2d_bsplinesyn.. Default="""
+ paramreg.steps['1'].window_length,
mandatory=False,
example=
"step=1,type=seg,algo=slicereg,metric=MeanSquares:step=2,type=im,algo=syn,metric=MI,iter=5,shrink=2"
)
parser.add_option(
name="-z",
type_value="int",
description=
"""size of z-padding to enable deformation at edges when using SyN.""",
mandatory=False,
default_value=param.padding)
parser.add_option(name="-x",
type_value="multiple_choice",
description="""Final interpolation.""",
mandatory=False,
default_value='linear',
example=['nn', 'linear', 'spline'])
parser.add_option(name="-r",
type_value="multiple_choice",
description="""Remove temporary files.""",
mandatory=False,
default_value='1',
example=['0', '1'])
parser.add_option(name="-v",
type_value="multiple_choice",
description="""Verbose.""",
mandatory=False,
default_value='1',
example=['0', '1', '2'])
arguments = parser.parse(sys.argv[1:])
# get arguments
fname_src = arguments['-i']
fname_dest = arguments['-d']
if '-iseg' in arguments:
fname_src_seg = arguments['-iseg']
if '-dseg' in arguments:
fname_dest_seg = arguments['-dseg']
if '-o' in arguments:
fname_output = arguments['-o']
if "-m" in arguments:
fname_mask = arguments['-m']
padding = arguments['-z']
if "-p" in arguments:
paramreg_user = arguments['-p']
# update registration parameters
for paramStep in paramreg_user:
paramreg.addStep(paramStep)
interp = arguments['-x']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
# Parameters for debug mode
if param.debug:
print '\n*** WARNING: DEBUG MODE ON ***\n'
status, path_sct_data = commands.getstatusoutput(
'echo $SCT_TESTING_DATA_DIR')
fname_dest = path_sct_data + '/mt/mt1.nii.gz'
fname_src = path_sct_data + '/t2/t2.nii.gz'
param_user = '******'
remove_temp_files = '0'
verbose = 1
# print arguments
print '\nInput parameters:'
print ' Source .............. ' + fname_src
print ' Destination ......... ' + fname_dest
print ' Mask ................ ' + fname_mask
print ' Output name ......... ' + fname_output
# print ' Algorithm ........... '+paramreg.algo
# print ' Number of iterations '+paramreg.iter
# print ' Metric .............. '+paramreg.metric
print ' Remove temp files ... ' + str(remove_temp_files)
print ' Verbose ............. ' + str(verbose)
# update param
param.verbose = verbose
param.padding = padding
param.fname_mask = fname_mask
param.remove_temp_files = remove_temp_files
# Get if input is 3D
sct.printv('\nCheck if input data are 3D...', verbose)
sct.check_if_3d(fname_src)
sct.check_if_3d(fname_dest)
# check if destination data is RPI
sct.printv('\nCheck if destination data is RPI...', verbose)
sct.check_if_rpi(fname_dest)
# Extract path, file and extension
path_src, file_src, ext_src = sct.extract_fname(fname_src)
path_dest, file_dest, ext_dest = sct.extract_fname(fname_dest)
# define output folder and file name
if fname_output == '':
path_out = '' # output in user's current directory
file_out = file_src + "_reg"
ext_out = ext_src
else:
path_out, file_out, ext_out = sct.extract_fname(fname_output)
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = 'tmp.' + time.strftime("%y%m%d%H%M%S")
status, output = sct.run('mkdir ' + path_tmp, verbose)
# copy files to temporary folder
sct.printv('\nCopy files...', verbose)
sct.run('isct_c3d ' + fname_src + ' -o ' + path_tmp + '/src.nii', verbose)
sct.run('isct_c3d ' + fname_dest + ' -o ' + path_tmp + '/dest.nii',
verbose)
if fname_src_seg:
sct.run(
'isct_c3d ' + fname_src_seg + ' -o ' + path_tmp + '/src_seg.nii',
verbose)
sct.run(
'isct_c3d ' + fname_dest_seg + ' -o ' + path_tmp + '/dest_seg.nii',
verbose)
if not fname_mask == '':
sct.run('isct_c3d ' + fname_mask + ' -o ' + path_tmp + '/mask.nii.gz',
verbose)
# go to tmp folder
os.chdir(path_tmp)
# Put source into destination space using header (no estimation -- purely based on header)
# TODO: use c3d?
# TODO: Check if necessary to do that
# TODO: use that as step=0
# sct.printv('\nPut source into destination space using header...', verbose)
# sct.run('isct_antsRegistration -d 3 -t Translation[0] -m MI[dest_pad.nii,src.nii,1,16] -c 0 -f 1 -s 0 -o [regAffine,src_regAffine.nii] -n BSpline[3]', verbose)
# if segmentation, also do it for seg
# loop across registration steps
warp_forward = []
warp_inverse = []
for i_step in range(0, len(paramreg.steps)):
sct.printv(
'\nEstimate transformation for step #' + str(i_step) + '...',
param.verbose)
# identify which is the src and dest
if paramreg.steps[str(i_step)].type == 'im':
src = 'src.nii'
dest = 'dest.nii'
interp_step = 'linear'
elif paramreg.steps[str(i_step)].type == 'seg':
src = 'src_seg.nii'
dest = 'dest_seg.nii'
interp_step = 'nn'
else:
sct.run('ERROR: Wrong image type.', 1, 'error')
# if step>0, apply warp_forward_concat to the src image to be used
if i_step > 0:
sct.run(
'sct_apply_transfo -i ' + src + ' -d ' + dest + ' -w ' +
','.join(warp_forward) + ' -o ' + sct.add_suffix(src, '_reg') +
' -x ' + interp_step, verbose)
src = sct.add_suffix(src, '_reg')
# register src --> dest
warp_forward_out, warp_inverse_out = register(src, dest, paramreg,
param, str(i_step))
warp_forward.append(warp_forward_out)
warp_inverse.append(warp_inverse_out)
# Put warp_forward_0 at the end of the list
warp_forward_0 = warp_forward.pop(0)
warp_forward.append(warp_forward_0)
# Concatenate transformations
sct.printv('\nConcatenate transformations...', verbose)
sct.run(
'sct_concat_transfo -w ' + ','.join(warp_forward) +
' -d dest.nii -o warp_src2dest.nii.gz', verbose)
warp_inverse.reverse()
sct.run(
'sct_concat_transfo -w ' + ','.join(warp_inverse) +
' -d dest.nii -o warp_dest2src.nii.gz', verbose)
# Apply warping field to src data
sct.printv('\nApply transfo source --> dest...', verbose)
sct.run(
'sct_apply_transfo -i src.nii -o src_reg.nii -d dest.nii -w warp_src2dest.nii.gz -x '
+ interp, verbose)
sct.printv('\nApply transfo dest --> source...', verbose)
sct.run(
'sct_apply_transfo -i dest.nii -o dest_reg.nii -d src.nii -w warp_dest2src.nii.gz -x '
+ interp, verbose)
# come back to parent folder
os.chdir('..')
# Generate output files
sct.printv('\nGenerate output files...', verbose)
fname_src2dest = sct.generate_output_file(path_tmp + '/src_reg.nii',
path_out + file_out + ext_out,
verbose)
sct.generate_output_file(
path_tmp + '/warp_src2dest.nii.gz',
path_out + 'warp_' + file_src + '2' + file_dest + '.nii.gz', verbose)
fname_dest2src = sct.generate_output_file(
path_tmp + '/dest_reg.nii', path_out + file_dest + '_reg' + ext_dest,
verbose)
sct.generate_output_file(
path_tmp + '/warp_dest2src.nii.gz',
path_out + 'warp_' + file_dest + '2' + file_src + '.nii.gz', verbose)
# sct.generate_output_file(path_tmp+'/warp_dest2src.nii.gz', path_out+'warp_dest2src.nii.gz')
# Delete temporary files
if remove_temp_files:
sct.printv('\nRemove temporary files...', verbose)
sct.run('rm -rf ' + path_tmp, verbose)
# display elapsed time
elapsed_time = time.time() - start_time
sct.printv(
'\nFinished! Elapsed time: ' + str(int(round(elapsed_time))) + 's',
verbose)
sct.printv('\nTo view results, type:', verbose)
sct.printv('fslview ' + fname_dest + ' ' + fname_src2dest + ' &', verbose,
'info')
sct.printv('fslview ' + fname_src + ' ' + fname_dest2src + ' &\n', verbose,
'info')
def run_main():
parser = Parser(__file__)
parser.usage.set_description(
"""This program will use the OptiC method to detect the spinal cord centerline."""
)
parser.add_option(name="-i",
type_value="image_nifti",
description="input image.",
mandatory=True,
example="t1.nii.gz")
parser.add_option(name="-c",
type_value="multiple_choice",
description="type of image contrast.",
mandatory=True,
example=['t1', 't2', 't2s', 'dwi'])
parser.add_option(name="-ofolder",
type_value="folder_creation",
description="output folder.",
mandatory=False,
example="My_Output_Folder/",
default_value="")
parser.add_option(
name="-roi",
type_value="multiple_choice",
description="outputs a ROI file, compatible with JIM software.",
mandatory=False,
example=['0', '1'],
default_value='0')
parser.add_option(name="-r",
type_value="multiple_choice",
description="remove temporary files.",
mandatory=False,
example=['0', '1'],
default_value='1')
parser.add_option(name="-v",
type_value="multiple_choice",
description="1: display on, 0: display off (default)",
mandatory=False,
example=["0", "1"],
default_value="1")
args = sys.argv[1:]
arguments = parser.parse(args)
# Input filename
fname_input_data = arguments["-i"]
fname_data = os.path.abspath(fname_input_data)
# Contrast type
contrast_type = arguments["-c"]
# Output folder
if "-ofolder" in arguments:
folder_output = sct.slash_at_the_end(arguments["-ofolder"], slash=1)
else:
folder_output = './'
# Remove temporary files
remove_temp_files = True
if "-r" in arguments:
remove_temp_files = bool(arguments["-r"])
# Outputs a ROI file
output_roi = False
if "-roi" in arguments:
output_roi = bool(arguments["-roi"])
# Verbosity
verbose = 0
if "-v" in arguments:
if arguments["-v"] is "1":
verbose = 2
# OptiC models
path_script = os.path.dirname(__file__)
path_sct = os.path.dirname(path_script)
optic_models_path = os.path.join(path_sct, 'data/optic_models',
'{}_model'.format(contrast_type))
# Execute OptiC binary
_, optic_filename = optic.detect_centerline(
image_fname=fname_data,
contrast_type=contrast_type,
optic_models_path=optic_models_path,
folder_output=folder_output,
remove_temp_files=remove_temp_files,
output_roi=output_roi,
verbose=verbose)
sct.printv('\nDone! To view results, type:', verbose)
sct.printv(
"fslview " + fname_input_data + " " + optic_filename +
" -l Red -b 0,1 -t 0.7 &\n", verbose, 'info')
def main():
# Initialization
fname_output = ''
fname_mask = param.fname_mask
fname_src_seg = ''
fsloutput = 'export FSLOUTPUTTYPE=NIFTI; ' # for faster processing, all outputs are in NIFTI'
start_time = time.time()
# get path of the toolbox
status, path_sct = commands.getstatusoutput('echo $SCT_DIR')
# get default registration parameters
# step1 = Paramreg(step='1', type='im', algo='syn', metric='MI', iter='5', shrink='1', smooth='0', gradStep='0.5')
step0 = Paramreg(step='0', type='im', algo='syn', metric='MI', iter='0', shrink='1', smooth='0', gradStep='0.5') # only used to put src into dest space
step1 = Paramreg()
paramreg = ParamregMultiStep([step0, step1])
# Initialize the parser
parser = Parser(__file__)
parser.usage.set_description('This program co-registers two 3D volumes. The deformation is non-rigid and is '
'constrained along Z direction (i.e., axial plane). Hence, this function assumes '
'that orientation of the destination image is axial (RPI). If you need to register '
'two volumes with large deformations and/or different contrasts, it is recommended to '
'input spinal cord segmentations (binary mask) in order to achieve maximum robustness.'
' The program outputs a warping field that can be used to register other images to the'
' destination image. To apply the warping field to another image, use '
'sct_apply_transfo')
parser.add_option(name="-i",
type_value="file",
description="Image source.",
mandatory=True,
example="src.nii.gz")
parser.add_option(name="-d",
type_value="file",
description="Image destination.",
mandatory=True,
example="dest.nii.gz")
parser.add_option(name="-iseg",
type_value="file",
description="Segmentation source.",
mandatory=False,
example="src_seg.nii.gz")
parser.add_option(name="-dseg",
type_value="file",
description="Segmentation destination.",
mandatory=False,
example="dest_seg.nii.gz")
parser.add_option(name="-m",
type_value="file",
description="Binary mask to improve accuracy over region of interest.",
mandatory=False,
example="mask.nii.gz")
parser.add_option(name="-o",
type_value="file_output",
description="Name of output file.",
mandatory=False,
example="src_reg.nii.gz")
parser.add_option(name="-p",
type_value=[[':'],'str'],
description="""Parameters for registration. Separate arguments with ",". Separate steps with ":".\nstep: <int> Step number (starts at 1).\ntype: {im,seg} type of data used for registration.\nalgo: {slicereg,rigid,affine,syn,bsplinesyn}. Default="""+paramreg.steps['1'].algo+"""\n For info about slicereg, see here: goo.gl/Sj3ZeU\nmetric: {CC,MI,MeanSquares}. Default="""+paramreg.steps['1'].metric+"""\niter: <int> Number of iterations. Default="""+paramreg.steps['1'].iter+"""\nshrink: <int> Shrink factor (only for SyN). Default="""+paramreg.steps['1'].shrink+"""\nsmooth: <int> Smooth factor (only for SyN). Default="""+paramreg.steps['1'].smooth+"""\ngradStep: <float> Gradient step (only for SyN). Default="""+paramreg.steps['1'].gradStep+"""\npoly: <int> Polynomial degree (only for slicereg). Default="""+paramreg.steps['1'].poly,
mandatory=False,
example="step=1,type=seg,algo=slicereg,metric=MeanSquares:step=2,type=im,algo=syn,metric=MI,iter=5,shrink=2")
parser.add_option(name="-z",
type_value="int",
description="""size of z-padding to enable deformation at edges when using SyN.""",
mandatory=False,
default_value=param.padding)
parser.add_option(name="-x",
type_value="multiple_choice",
description="""Final interpolation.""",
mandatory=False,
default_value='linear',
example=['nn', 'linear', 'spline'])
parser.add_option(name="-r",
type_value="multiple_choice",
description="""Remove temporary files.""",
mandatory=False,
default_value='1',
example=['0', '1'])
parser.add_option(name="-v",
type_value="multiple_choice",
description="""Verbose.""",
mandatory=False,
default_value='1',
example=['0', '1', '2'])
arguments = parser.parse(sys.argv[1:])
# get arguments
fname_src = arguments['-i']
fname_dest = arguments['-d']
if '-iseg' in arguments:
fname_src_seg = arguments['-iseg']
if '-dseg' in arguments:
fname_dest_seg = arguments['-dseg']
if '-o' in arguments:
fname_output = arguments['-o']
if "-m" in arguments:
fname_mask = arguments['-m']
padding = arguments['-z']
if "-p" in arguments:
paramreg_user = arguments['-p']
# update registration parameters
for paramStep in paramreg_user:
paramreg.addStep(paramStep)
interp = arguments['-x']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
# Parameters for debug mode
if param.debug:
print '\n*** WARNING: DEBUG MODE ON ***\n'
status, path_sct_data = commands.getstatusoutput('echo $SCT_TESTING_DATA_DIR')
fname_dest = path_sct_data+'/mt/mt1.nii.gz'
fname_src = path_sct_data+'/t2/t2.nii.gz'
param_user = '******'
remove_temp_files = '0'
verbose = 1
# print arguments
print '\nInput parameters:'
print ' Source .............. '+fname_src
print ' Destination ......... '+fname_dest
print ' Mask ................ '+fname_mask
print ' Output name ......... '+fname_output
# print ' Algorithm ........... '+paramreg.algo
# print ' Number of iterations '+paramreg.iter
# print ' Metric .............. '+paramreg.metric
print ' Remove temp files ... '+str(remove_temp_files)
print ' Verbose ............. '+str(verbose)
# update param
param.verbose = verbose
param.padding = padding
param.fname_mask = fname_mask
# Get if input is 3D
sct.printv('\nCheck if input data are 3D...', verbose)
sct.check_if_3d(fname_src)
sct.check_if_3d(fname_dest)
# check if destination data is RPI
sct.printv('\nCheck if destination data is RPI...', verbose)
sct.check_if_rpi(fname_dest)
# Extract path, file and extension
path_src, file_src, ext_src = sct.extract_fname(fname_src)
path_dest, file_dest, ext_dest = sct.extract_fname(fname_dest)
# define output folder and file name
if fname_output == '':
path_out = '' # output in user's current directory
file_out = file_src+"_reg"
ext_out = ext_src
else:
path_out, file_out, ext_out = sct.extract_fname(fname_output)
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = 'tmp.'+time.strftime("%y%m%d%H%M%S")
status, output = sct.run('mkdir '+path_tmp, verbose)
# copy files to temporary folder
sct.printv('\nCopy files...', verbose)
sct.run('isct_c3d '+fname_src+' -o '+path_tmp+'/src.nii', verbose)
sct.run('isct_c3d '+fname_dest+' -o '+path_tmp+'/dest.nii', verbose)
if fname_src_seg:
sct.run('isct_c3d '+fname_src_seg+' -o '+path_tmp+'/src_seg.nii', verbose)
sct.run('isct_c3d '+fname_dest_seg+' -o '+path_tmp+'/dest_seg.nii', verbose)
if not fname_mask == '':
sct.run('isct_c3d '+fname_mask+' -o '+path_tmp+'/mask.nii.gz', verbose)
# go to tmp folder
os.chdir(path_tmp)
# Put source into destination space using header (no estimation -- purely based on header)
# TODO: use c3d?
# TODO: Check if necessary to do that
# TODO: use that as step=0
# sct.printv('\nPut source into destination space using header...', verbose)
# sct.run('isct_antsRegistration -d 3 -t Translation[0] -m MI[dest_pad.nii,src.nii,1,16] -c 0 -f 1 -s 0 -o [regAffine,src_regAffine.nii] -n BSpline[3]', verbose)
# if segmentation, also do it for seg
# loop across registration steps
warp_forward = []
warp_inverse = []
for i_step in range(0, len(paramreg.steps)):
sct.printv('\nEstimate transformation for step #'+str(i_step)+'...', param.verbose)
# identify which is the src and dest
if paramreg.steps[str(i_step)].type == 'im':
src = 'src.nii'
dest = 'dest.nii'
interp_step = 'linear'
elif paramreg.steps[str(i_step)].type == 'seg':
src = 'src_seg.nii'
dest = 'dest_seg.nii'
interp_step = 'nn'
else:
sct.run('ERROR: Wrong image type.', 1, 'error')
# if step>0, apply warp_forward_concat to the src image to be used
if i_step > 0:
sct.run('sct_apply_transfo -i '+src+' -d '+dest+' -w '+','.join(warp_forward)+' -o '+sct.add_suffix(src, '_reg')+' -x '+interp_step, verbose)
src = sct.add_suffix(src, '_reg')
# register src --> dest
warp_forward_out, warp_inverse_out = register(src, dest, paramreg, param, str(i_step))
warp_forward.append(warp_forward_out)
warp_inverse.append(warp_inverse_out)
# Concatenate transformations
sct.printv('\nConcatenate transformations...', verbose)
sct.run('sct_concat_transfo -w '+','.join(warp_forward)+' -d dest.nii -o warp_src2dest.nii.gz', verbose)
warp_inverse.reverse()
sct.run('sct_concat_transfo -w '+','.join(warp_inverse)+' -d dest.nii -o warp_dest2src.nii.gz', verbose)
# Apply warping field to src data
sct.printv('\nApply transfo source --> dest...', verbose)
sct.run('sct_apply_transfo -i src.nii -o src_reg.nii -d dest.nii -w warp_src2dest.nii.gz -x '+interp, verbose)
sct.printv('\nApply transfo dest --> source...', verbose)
sct.run('sct_apply_transfo -i dest.nii -o dest_reg.nii -d src.nii -w warp_dest2src.nii.gz -x '+interp, verbose)
# come back to parent folder
os.chdir('..')
# Generate output files
sct.printv('\nGenerate output files...', verbose)
fname_src2dest = sct.generate_output_file(path_tmp+'/src_reg.nii', path_out+file_out+ext_out, verbose)
sct.generate_output_file(path_tmp+'/warp_src2dest.nii.gz', path_out+'warp_'+file_src+'2'+file_dest+'.nii.gz', verbose)
fname_dest2src = sct.generate_output_file(path_tmp+'/dest_reg.nii', path_out+file_dest+'_reg'+ext_dest, verbose)
sct.generate_output_file(path_tmp+'/warp_dest2src.nii.gz', path_out+'warp_'+file_dest+'2'+file_src+'.nii.gz', verbose)
# sct.generate_output_file(path_tmp+'/warp_dest2src.nii.gz', path_out+'warp_dest2src.nii.gz')
# Delete temporary files
if remove_temp_files:
sct.printv('\nRemove temporary files...', verbose)
sct.run('rm -rf '+path_tmp, verbose)
# display elapsed time
elapsed_time = time.time() - start_time
sct.printv('\nFinished! Elapsed time: '+str(int(round(elapsed_time)))+'s', verbose)
sct.printv('\nTo view results, type:', verbose)
sct.printv('fslview '+fname_dest+' '+fname_src2dest+' &', verbose, 'info')
sct.printv('fslview '+fname_src+' '+fname_dest2src+' &\n', verbose, 'info')
def main():
# get default parameters
step1 = Paramreg(step='1', type='seg', algo='slicereg', metric='MeanSquares', iter='10')
step2 = Paramreg(step='2', type='im', algo='syn', metric='MI', iter='3')
# step1 = Paramreg()
paramreg = ParamregMultiStep([step1, step2])
# step1 = Paramreg_step(step='1', type='seg', algo='bsplinesyn', metric='MeanSquares', iter='10', shrink='1', smooth='0', gradStep='0.5')
# step2 = Paramreg_step(step='2', type='im', algo='syn', metric='MI', iter='10', shrink='1', smooth='0', gradStep='0.5')
# paramreg = ParamregMultiStep([step1, step2])
# Initialize the parser
parser = Parser(__file__)
parser.usage.set_description('Register anatomical image to the template.')
parser.add_option(name="-i",
type_value="file",
description="Anatomical image.",
mandatory=True,
example="anat.nii.gz")
parser.add_option(name="-s",
type_value="file",
description="Spinal cord segmentation.",
mandatory=True,
example="anat_seg.nii.gz")
parser.add_option(name="-l",
type_value="file",
description="Labels. See: http://sourceforge.net/p/spinalcordtoolbox/wiki/create_labels/",
mandatory=True,
default_value='',
example="anat_labels.nii.gz")
parser.add_option(name="-t",
type_value="folder",
description="Path to MNI-Poly-AMU template.",
mandatory=False,
default_value=param.path_template)
parser.add_option(name="-p",
type_value=[[':'], 'str'],
description="""Parameters for registration (see sct_register_multimodal). Default:\n--\nstep=1\ntype="""+paramreg.steps['1'].type+"""\nalgo="""+paramreg.steps['1'].algo+"""\nmetric="""+paramreg.steps['1'].metric+"""\npoly="""+paramreg.steps['1'].poly+"""\n--\nstep=2\ntype="""+paramreg.steps['2'].type+"""\nalgo="""+paramreg.steps['2'].algo+"""\nmetric="""+paramreg.steps['2'].metric+"""\niter="""+paramreg.steps['2'].iter+"""\nshrink="""+paramreg.steps['2'].shrink+"""\nsmooth="""+paramreg.steps['2'].smooth+"""\ngradStep="""+paramreg.steps['2'].gradStep+"""\n--""",
mandatory=False,
example="step=2,type=seg,algo=bsplinesyn,metric=MeanSquares,iter=5,shrink=2:step=3,type=im,algo=syn,metric=MI,iter=5,shrink=1,gradStep=0.3")
parser.add_option(name="-r",
type_value="multiple_choice",
description="""Remove temporary files.""",
mandatory=False,
default_value='1',
example=['0', '1'])
parser.add_option(name="-v",
type_value="multiple_choice",
description="""Verbose. 0: nothing. 1: basic. 2: extended.""",
mandatory=False,
default_value=param.verbose,
example=['0', '1', '2'])
if param.debug:
print '\n*** WARNING: DEBUG MODE ON ***\n'
fname_data = '/Users/julien/data/temp/sct_example_data/t2/t2.nii.gz'
fname_landmarks = '/Users/julien/data/temp/sct_example_data/t2/labels.nii.gz'
fname_seg = '/Users/julien/data/temp/sct_example_data/t2/t2_seg.nii.gz'
path_template = param.path_template
remove_temp_files = 0
verbose = 2
# speed = 'superfast'
#param_reg = '2,BSplineSyN,0.6,MeanSquares'
else:
arguments = parser.parse(sys.argv[1:])
# get arguments
fname_data = arguments['-i']
fname_seg = arguments['-s']
fname_landmarks = arguments['-l']
path_template = arguments['-t']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
if '-p' in arguments:
paramreg_user = arguments['-p']
# update registration parameters
for paramStep in paramreg_user:
paramreg.addStep(paramStep)
# initialize other parameters
file_template = param.file_template
file_template_label = param.file_template_label
file_template_seg = param.file_template_seg
output_type = param.output_type
zsubsample = param.zsubsample
# smoothing_sigma = param.smoothing_sigma
# start timer
start_time = time.time()
# get absolute path - TO DO: remove! NEVER USE ABSOLUTE PATH...
path_template = os.path.abspath(path_template)
# get fname of the template + template objects
fname_template = sct.slash_at_the_end(path_template, 1)+file_template
fname_template_label = sct.slash_at_the_end(path_template, 1)+file_template_label
fname_template_seg = sct.slash_at_the_end(path_template, 1)+file_template_seg
# check file existence
sct.printv('\nCheck template files...')
sct.check_file_exist(fname_template, verbose)
sct.check_file_exist(fname_template_label, verbose)
sct.check_file_exist(fname_template_seg, verbose)
# print arguments
sct.printv('\nCheck parameters:', verbose)
sct.printv('.. Data: '+fname_data, verbose)
sct.printv('.. Landmarks: '+fname_landmarks, verbose)
sct.printv('.. Segmentation: '+fname_seg, verbose)
sct.printv('.. Path template: '+path_template, verbose)
sct.printv('.. Output type: '+str(output_type), verbose)
sct.printv('.. Remove temp files: '+str(remove_temp_files), verbose)
sct.printv('\nParameters for registration:')
for pStep in range(1, len(paramreg.steps)+1):
sct.printv('Step #'+paramreg.steps[str(pStep)].step, verbose)
sct.printv('.. Type #'+paramreg.steps[str(pStep)].type, verbose)
sct.printv('.. Algorithm................ '+paramreg.steps[str(pStep)].algo, verbose)
sct.printv('.. Metric................... '+paramreg.steps[str(pStep)].metric, verbose)
sct.printv('.. Number of iterations..... '+paramreg.steps[str(pStep)].iter, verbose)
sct.printv('.. Shrink factor............ '+paramreg.steps[str(pStep)].shrink, verbose)
sct.printv('.. Smoothing factor......... '+paramreg.steps[str(pStep)].smooth, verbose)
sct.printv('.. Gradient step............ '+paramreg.steps[str(pStep)].gradStep, verbose)
sct.printv('.. Degree of polynomial..... '+paramreg.steps[str(pStep)].poly, verbose)
path_data, file_data, ext_data = sct.extract_fname(fname_data)
sct.printv('\nCheck input labels...')
# check if label image contains coherent labels
image_label = Image(fname_landmarks)
# -> all labels must be different
labels = image_label.getNonZeroCoordinates()
hasDifferentLabels = True
for lab in labels:
for otherlabel in labels:
if lab != otherlabel and lab.hasEqualValue(otherlabel):
hasDifferentLabels = False
break
if not hasDifferentLabels:
sct.printv('ERROR: Wrong landmarks input. All labels must be different.', verbose, 'error')
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = 'tmp.'+time.strftime("%y%m%d%H%M%S")
status, output = sct.run('mkdir '+path_tmp)
# copy files to temporary folder
sct.printv('\nCopy files...', verbose)
sct.run('isct_c3d '+fname_data+' -o '+path_tmp+'/data.nii')
sct.run('isct_c3d '+fname_landmarks+' -o '+path_tmp+'/landmarks.nii.gz')
sct.run('isct_c3d '+fname_seg+' -o '+path_tmp+'/segmentation.nii.gz')
sct.run('isct_c3d '+fname_template+' -o '+path_tmp+'/template.nii')
sct.run('isct_c3d '+fname_template_label+' -o '+path_tmp+'/template_labels.nii.gz')
sct.run('isct_c3d '+fname_template_seg+' -o '+path_tmp+'/template_seg.nii.gz')
# go to tmp folder
os.chdir(path_tmp)
# Change orientation of input images to RPI
sct.printv('\nChange orientation of input images to RPI...', verbose)
set_orientation('data.nii', 'RPI', 'data_rpi.nii')
set_orientation('landmarks.nii.gz', 'RPI', 'landmarks_rpi.nii.gz')
set_orientation('segmentation.nii.gz', 'RPI', 'segmentation_rpi.nii.gz')
# crop segmentation
# output: segmentation_rpi_crop.nii.gz
sct.run('sct_crop_image -i segmentation_rpi.nii.gz -o segmentation_rpi_crop.nii.gz -dim 2 -bzmax')
# straighten segmentation
sct.printv('\nStraighten the spinal cord using centerline/segmentation...', verbose)
sct.run('sct_straighten_spinalcord -i segmentation_rpi_crop.nii.gz -c segmentation_rpi_crop.nii.gz -r 0')
# Label preparation:
# --------------------------------------------------------------------------------
# Remove unused label on template. Keep only label present in the input label image
sct.printv('\nRemove unused label on template. Keep only label present in the input label image...', verbose)
sct.run('sct_label_utils -t remove -i template_labels.nii.gz -o template_label.nii.gz -r landmarks_rpi.nii.gz')
# Make sure landmarks are INT
sct.printv('\nConvert landmarks to INT...', verbose)
sct.run('isct_c3d template_label.nii.gz -type int -o template_label.nii.gz', verbose)
# Create a cross for the template labels - 5 mm
sct.printv('\nCreate a 5 mm cross for the template labels...', verbose)
sct.run('sct_label_utils -t cross -i template_label.nii.gz -o template_label_cross.nii.gz -c 5')
# Create a cross for the input labels and dilate for straightening preparation - 5 mm
sct.printv('\nCreate a 5mm cross for the input labels and dilate for straightening preparation...', verbose)
sct.run('sct_label_utils -t cross -i landmarks_rpi.nii.gz -o landmarks_rpi_cross3x3.nii.gz -c 5 -d')
# Apply straightening to labels
sct.printv('\nApply straightening to labels...', verbose)
sct.run('sct_apply_transfo -i landmarks_rpi_cross3x3.nii.gz -o landmarks_rpi_cross3x3_straight.nii.gz -d segmentation_rpi_crop_straight.nii.gz -w warp_curve2straight.nii.gz -x nn')
# Convert landmarks from FLOAT32 to INT
sct.printv('\nConvert landmarks from FLOAT32 to INT...', verbose)
sct.run('isct_c3d landmarks_rpi_cross3x3_straight.nii.gz -type int -o landmarks_rpi_cross3x3_straight.nii.gz')
# Estimate affine transfo: straight --> template (landmark-based)'
sct.printv('\nEstimate affine transfo: straight anat --> template (landmark-based)...', verbose)
sct.run('isct_ANTSUseLandmarkImagesToGetAffineTransform template_label_cross.nii.gz landmarks_rpi_cross3x3_straight.nii.gz affine straight2templateAffine.txt')
# Apply affine transformation: straight --> template
sct.printv('\nApply affine transformation: straight --> template...', verbose)
sct.run('sct_concat_transfo -w warp_curve2straight.nii.gz,straight2templateAffine.txt -d template.nii -o warp_curve2straightAffine.nii.gz')
sct.run('sct_apply_transfo -i data_rpi.nii -o data_rpi_straight2templateAffine.nii -d template.nii -w warp_curve2straightAffine.nii.gz')
sct.run('sct_apply_transfo -i segmentation_rpi.nii.gz -o segmentation_rpi_straight2templateAffine.nii.gz -d template.nii -w warp_curve2straightAffine.nii.gz -x linear')
# find min-max of anat2template (for subsequent cropping)
sct.run('export FSLOUTPUTTYPE=NIFTI; fslmaths segmentation_rpi_straight2templateAffine.nii.gz -thr 0.5 segmentation_rpi_straight2templateAffine_th.nii.gz', param.verbose)
zmin_template, zmax_template = find_zmin_zmax('segmentation_rpi_straight2templateAffine_th.nii.gz')
# crop template in z-direction (for faster processing)
sct.printv('\nCrop data in template space (for faster processing)...', verbose)
sct.run('sct_crop_image -i template.nii -o template_crop.nii -dim 2 -start '+str(zmin_template)+' -end '+str(zmax_template))
sct.run('sct_crop_image -i template_seg.nii.gz -o template_seg_crop.nii.gz -dim 2 -start '+str(zmin_template)+' -end '+str(zmax_template))
sct.run('sct_crop_image -i data_rpi_straight2templateAffine.nii -o data_rpi_straight2templateAffine_crop.nii -dim 2 -start '+str(zmin_template)+' -end '+str(zmax_template))
sct.run('sct_crop_image -i segmentation_rpi_straight2templateAffine.nii.gz -o segmentation_rpi_straight2templateAffine_crop.nii.gz -dim 2 -start '+str(zmin_template)+' -end '+str(zmax_template))
# sub-sample in z-direction
sct.printv('\nSub-sample in z-direction (for faster processing)...', verbose)
sct.run('sct_resample -i template_crop.nii -o template_crop_r.nii -f 1x1x'+zsubsample, verbose)
sct.run('sct_resample -i template_seg_crop.nii.gz -o template_seg_crop_r.nii.gz -f 1x1x'+zsubsample, verbose)
sct.run('sct_resample -i data_rpi_straight2templateAffine_crop.nii -o data_rpi_straight2templateAffine_crop_r.nii -f 1x1x'+zsubsample, verbose)
sct.run('sct_resample -i segmentation_rpi_straight2templateAffine_crop.nii.gz -o segmentation_rpi_straight2templateAffine_crop_r.nii.gz -f 1x1x'+zsubsample, verbose)
# Registration straight spinal cord to template
sct.printv('\nRegister straight spinal cord to template...', verbose)
# loop across registration steps
warp_forward = []
warp_inverse = []
for i_step in range(1, len(paramreg.steps)+1):
sct.printv('\nEstimate transformation for step #'+str(i_step)+'...', verbose)
# identify which is the src and dest
if paramreg.steps[str(i_step)].type == 'im':
src = 'data_rpi_straight2templateAffine_crop_r.nii'
dest = 'template_crop_r.nii'
interp_step = 'linear'
elif paramreg.steps[str(i_step)].type == 'seg':
src = 'segmentation_rpi_straight2templateAffine_crop_r.nii.gz'
dest = 'template_seg_crop_r.nii.gz'
interp_step = 'nn'
else:
sct.run('ERROR: Wrong image type.', 1, 'error')
# if step>1, apply warp_forward_concat to the src image to be used
if i_step > 1:
# sct.run('sct_apply_transfo -i '+src+' -d '+dest+' -w '+','.join(warp_forward)+' -o '+sct.add_suffix(src, '_reg')+' -x '+interp_step, verbose)
sct.run('sct_apply_transfo -i '+src+' -d '+dest+' -w '+','.join(warp_forward)+' -o '+sct.add_suffix(src, '_reg')+' -x '+interp_step, verbose)
src = sct.add_suffix(src, '_reg')
# register src --> dest
warp_forward_out, warp_inverse_out = register(src, dest, paramreg, param, str(i_step))
warp_forward.append(warp_forward_out)
warp_inverse.append(warp_inverse_out)
# Concatenate transformations:
sct.printv('\nConcatenate transformations: anat --> template...', verbose)
sct.run('sct_concat_transfo -w warp_curve2straightAffine.nii.gz,'+','.join(warp_forward)+' -d template.nii -o warp_anat2template.nii.gz', verbose)
# sct.run('sct_concat_transfo -w warp_curve2straight.nii.gz,straight2templateAffine.txt,'+','.join(warp_forward)+' -d template.nii -o warp_anat2template.nii.gz', verbose)
warp_inverse.reverse()
sct.run('sct_concat_transfo -w '+','.join(warp_inverse)+',-straight2templateAffine.txt,warp_straight2curve.nii.gz -d data.nii -o warp_template2anat.nii.gz', verbose)
# Apply warping fields to anat and template
if output_type == 1:
sct.run('sct_apply_transfo -i template.nii -o template2anat.nii.gz -d data.nii -w warp_template2anat.nii.gz -c 1', verbose)
sct.run('sct_apply_transfo -i data.nii -o anat2template.nii.gz -d template.nii -w warp_anat2template.nii.gz -c 1', verbose)
# come back to parent folder
os.chdir('..')
# Generate output files
sct.printv('\nGenerate output files...', verbose)
sct.generate_output_file(path_tmp+'/warp_template2anat.nii.gz', 'warp_template2anat.nii.gz', verbose)
sct.generate_output_file(path_tmp+'/warp_anat2template.nii.gz', 'warp_anat2template.nii.gz', verbose)
if output_type == 1:
sct.generate_output_file(path_tmp+'/template2anat.nii.gz', 'template2anat'+ext_data, verbose)
sct.generate_output_file(path_tmp+'/anat2template.nii.gz', 'anat2template'+ext_data, verbose)
# Delete temporary files
if remove_temp_files:
sct.printv('\nDelete temporary files...', verbose)
sct.run('rm -rf '+path_tmp)
# display elapsed time
elapsed_time = time.time() - start_time
sct.printv('\nFinished! Elapsed time: '+str(int(round(elapsed_time)))+'s', verbose)
# to view results
sct.printv('\nTo view results, type:', verbose)
sct.printv('fslview '+fname_data+' template2anat -b 0,4000 &', verbose, 'info')
sct.printv('fslview '+fname_template+' -b 0,5000 anat2template &\n', verbose, 'info')
def main():
# Initialization
fsloutputdir = 'export FSLOUTPUTTYPE=NIFTI_GZ; '
file_ordering = 'alternate'
start_time = time.time()
# # get path of the toolbox
# status, path_sct = commands.getstatusoutput('echo $SCT_DIR')
# Initialize the parser
parser = Parser(__file__)
parser.usage.set_description(
'Convert dcm2nii using nin sequence from J. Finsterbusch. '
'Requires the software dcm2nii (from mricron).')
parser.add_option(name="-i",
type_value="folder",
description="Path to dicom data.",
mandatory=True,
example="data/my_data")
parser.add_option(
name="-ord",
type_value="multiple_choice",
description=
"""File ordering: \nalternate: spine,brain,spine,brain... (with custom coil)\nbloc: spine,spine... brain,brain... (with head-neck coil)\n""",
mandatory=False,
default_value='bloc',
example=['alternate', 'bloc'])
parser.add_option(name="-r",
type_value="multiple_choice",
description="""Remove temporary files.""",
mandatory=False,
default_value='1',
example=['0', '1'])
parser.add_option(name="-v",
type_value="multiple_choice",
description="""Verbose.""",
mandatory=False,
default_value='1',
example=['0', '1', '2'])
arguments = parser.parse(sys.argv[1:])
# get arguments
path_data = sct.slash_at_the_end(arguments['-i'], 1)
if '-ord' in arguments:
file_ordering = arguments['-ord']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
# list all DICOM files
fname_data = os.listdir(path_data)
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = 'tmp.' + time.strftime("%y%m%d%H%M%S")
status, output = sct.run('mkdir ' + path_tmp, verbose)
# go to temporary folder
os.chdir(path_tmp)
# list DICOM files
file_data_list = os.listdir(path_data)
# create another temp folder for conversion
sct.run('mkdir tmp', verbose)
# loop across files
file_nii = []
i = 0
for i_file in file_data_list:
# convert dicom to nifti and put in temporary folder
status, output = sct.run('dcm2nii -o tmp/ -v n ' + path_data + i_file,
verbose)
# change file name
file_nii.append('data_' + str(i).zfill(4) + '.nii.gz')
sct.run('mv tmp/*.nii.gz ' + file_nii[i])
# increment file index
i = i + 1
# Merge data
nb_files = len(file_data_list)
if file_ordering == 'alternate':
sct.run(fsloutputdir + 'fslmerge -t data_spine ' +
' '.join([file_nii[i] for i in range(0, nb_files, 2)]))
sct.run(fsloutputdir + 'fslmerge -t data_brain ' +
' '.join([file_nii[i] for i in range(1, nb_files, 2)]))
if file_ordering == 'bloc':
sct.run(fsloutputdir + 'fslmerge -t data_spine ' +
' '.join([file_nii[i] for i in range(0, nb_files / 2)]))
sct.run(
fsloutputdir + 'fslmerge -t data_brain ' +
' '.join([file_nii[i] for i in range(nb_files / 2 + 1, nb_files)]))
# come back to parent folder
os.chdir('..')
# Generate output files
sct.printv('\nGenerate output files...', verbose)
fname_data_spine = sct.generate_output_file(
path_tmp + '/data_spine.nii.gz', 'data_spine.nii.gz', verbose)
fname_data_brain = sct.generate_output_file(
path_tmp + '/data_brain.nii.gz', 'data_brain.nii.gz', verbose)
# Delete temporary files
if remove_temp_files:
sct.printv('\nRemove temporary files...', verbose)
sct.run('rm -rf ' + path_tmp, verbose)
elapsed_time = time.time() - start_time
sct.printv(
'\nFinished! Elapsed time: ' + str(int(round(elapsed_time))) + 's',
verbose)
sct.printv('\nTo view results, type:', verbose)
sct.printv('fslview data_spine &', verbose, 'info')
sct.printv('fslview data_brain &\n', verbose, 'info')
def main():
# Initialization
fsloutputdir = 'export FSLOUTPUTTYPE=NIFTI_GZ; '
file_ordering = 'alternate'
start_time = time.time()
# Initialize the parser
parser = Parser(__file__)
parser.usage.set_description('Convert dcm2nii using nin sequence from J. Finsterbusch. '
'Requires the software dcm2nii (from mricron).')
parser.add_option(name="-i",
type_value="folder",
description="Path to dicom data.",
mandatory=True,
example="data/my_data")
parser.add_option(name="-ord",
type_value="multiple_choice",
description="""File ordering: \nalternate: spine,brain,spine,brain... (with custom coil)\nbloc: spine,spine... brain,brain... (with head-neck coil)\n""",
mandatory=False,
default_value='bloc',
example=['alternate', 'bloc'])
parser.add_option(name="-r",
type_value="multiple_choice",
description="""Remove temporary files.""",
mandatory=False,
default_value='1',
example=['0', '1'])
parser.add_option(name="-v",
type_value="multiple_choice",
description="""Verbose.""",
mandatory=False,
default_value='1',
example=['0', '1', '2'])
arguments = parser.parse(sys.argv[1:])
# get arguments
path_data = arguments['-i']
if '-ord' in arguments:
file_ordering = arguments['-ord']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
path_tmp = sct.tmp_create(basename="nin_convert_dcm2nii", verbose=verbose)
# go to temporary folder
curdir = os.getcwd()
os.chdir(path_tmp)
# list DICOM files
file_data_list = os.listdir(path_data)
# create another temp folder for conversion
sct.run('mkdir tmp', verbose)
# loop across files
file_nii = []
i = 0
for i_file in file_data_list:
# convert dicom to nifti and put in temporary folder
status, output = sct.run('dcm2nii -o tmp/ -v n '+os.path.join(path_data, i_file), verbose)
# change file name
file_nii.append('data_'+str(i).zfill(4)+'.nii.gz')
sct.run('mv tmp/*.nii.gz '+file_nii[i])
# increment file index
i = i+1
# Merge data
nb_files = len(file_data_list)
if file_ordering == 'alternate':
sct.run(fsloutputdir+'fslmerge -t data_spine '+' '.join([file_nii[i] for i in range(0, nb_files, 2)]))
sct.run(fsloutputdir+'fslmerge -t data_brain '+' '.join([file_nii[i] for i in range(1, nb_files, 2)]))
if file_ordering == 'bloc':
sct.run(fsloutputdir+'fslmerge -t data_spine '+' '.join([file_nii[i] for i in range(0, nb_files/2)]))
sct.run(fsloutputdir+'fslmerge -t data_brain '+' '.join([file_nii[i] for i in range(nb_files/2+1, nb_files)]))
# come back
os.chdir(curdir)
# Generate output files
sct.printv('\nGenerate output files...', verbose)
fname_data_spine = sct.generate_output_file(os.path.join(path_tmp, 'data_spine.nii.gz'), 'data_spine.nii.gz', verbose)
fname_data_brain = sct.generate_output_file(os.path.join(path_tmp, 'data_brain.nii.gz'), 'data_brain.nii.gz', verbose)
# Delete temporary files
if remove_temp_files:
sct.printv('\nRemove temporary files...', verbose)
sct.run('rm -rf '+path_tmp, verbose)
elapsed_time = time.time() - start_time
sct.printv('\nFinished! Elapsed time: '+str(int(round(elapsed_time)))+'s', verbose)
sct.printv('\nTo view results, type:', verbose)
sct.printv('fslview data_spine &', verbose, 'info')
sct.printv('fslview data_brain &\n', verbose, 'info')
def main():
# get default parameters
step1 = Paramreg(step='1',
type='seg',
algo='slicereg',
metric='MeanSquares',
iter='10')
step2 = Paramreg(step='2', type='im', algo='syn', metric='MI', iter='3')
# step1 = Paramreg()
paramreg = ParamregMultiStep([step1, step2])
# step1 = Paramreg_step(step='1', type='seg', algo='bsplinesyn', metric='MeanSquares', iter='10', shrink='1', smooth='0', gradStep='0.5')
# step2 = Paramreg_step(step='2', type='im', algo='syn', metric='MI', iter='10', shrink='1', smooth='0', gradStep='0.5')
# paramreg = ParamregMultiStep([step1, step2])
# Initialize the parser
parser = Parser(__file__)
parser.usage.set_description('Register anatomical image to the template.')
parser.add_option(name="-i",
type_value="file",
description="Anatomical image.",
mandatory=True,
example="anat.nii.gz")
parser.add_option(name="-s",
type_value="file",
description="Spinal cord segmentation.",
mandatory=True,
example="anat_seg.nii.gz")
parser.add_option(
name="-l",
type_value="file",
description=
"Labels. See: http://sourceforge.net/p/spinalcordtoolbox/wiki/create_labels/",
mandatory=True,
default_value='',
example="anat_labels.nii.gz")
parser.add_option(name="-t",
type_value="folder",
description="Path to MNI-Poly-AMU template.",
mandatory=False,
default_value=param.path_template)
parser.add_option(
name="-p",
type_value=[[':'], 'str'],
description=
"""Parameters for registration (see sct_register_multimodal). Default:\n--\nstep=1\ntype="""
+ paramreg.steps['1'].type + """\nalgo=""" + paramreg.steps['1'].algo +
"""\nmetric=""" + paramreg.steps['1'].metric + """\npoly=""" +
paramreg.steps['1'].poly + """\n--\nstep=2\ntype=""" +
paramreg.steps['2'].type + """\nalgo=""" + paramreg.steps['2'].algo +
"""\nmetric=""" + paramreg.steps['2'].metric + """\niter=""" +
paramreg.steps['2'].iter + """\nshrink=""" +
paramreg.steps['2'].shrink + """\nsmooth=""" +
paramreg.steps['2'].smooth + """\ngradStep=""" +
paramreg.steps['2'].gradStep + """\n--""",
mandatory=False,
example=
"step=2,type=seg,algo=bsplinesyn,metric=MeanSquares,iter=5,shrink=2:step=3,type=im,algo=syn,metric=MI,iter=5,shrink=1,gradStep=0.3"
)
parser.add_option(name="-r",
type_value="multiple_choice",
description="""Remove temporary files.""",
mandatory=False,
default_value='1',
example=['0', '1'])
parser.add_option(
name="-v",
type_value="multiple_choice",
description="""Verbose. 0: nothing. 1: basic. 2: extended.""",
mandatory=False,
default_value=param.verbose,
example=['0', '1', '2'])
if param.debug:
print '\n*** WARNING: DEBUG MODE ON ***\n'
fname_data = '/Users/julien/data/temp/sct_example_data/t2/t2.nii.gz'
fname_landmarks = '/Users/julien/data/temp/sct_example_data/t2/labels.nii.gz'
fname_seg = '/Users/julien/data/temp/sct_example_data/t2/t2_seg.nii.gz'
path_template = param.path_template
remove_temp_files = 0
verbose = 2
# speed = 'superfast'
#param_reg = '2,BSplineSyN,0.6,MeanSquares'
else:
arguments = parser.parse(sys.argv[1:])
# get arguments
fname_data = arguments['-i']
fname_seg = arguments['-s']
fname_landmarks = arguments['-l']
path_template = arguments['-t']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
if '-p' in arguments:
paramreg_user = arguments['-p']
# update registration parameters
for paramStep in paramreg_user:
paramreg.addStep(paramStep)
# initialize other parameters
file_template = param.file_template
file_template_label = param.file_template_label
file_template_seg = param.file_template_seg
output_type = param.output_type
zsubsample = param.zsubsample
# smoothing_sigma = param.smoothing_sigma
# start timer
start_time = time.time()
# get absolute path - TO DO: remove! NEVER USE ABSOLUTE PATH...
path_template = os.path.abspath(path_template)
# get fname of the template + template objects
fname_template = sct.slash_at_the_end(path_template, 1) + file_template
fname_template_label = sct.slash_at_the_end(path_template,
1) + file_template_label
fname_template_seg = sct.slash_at_the_end(path_template,
1) + file_template_seg
# check file existence
sct.printv('\nCheck template files...')
sct.check_file_exist(fname_template, verbose)
sct.check_file_exist(fname_template_label, verbose)
sct.check_file_exist(fname_template_seg, verbose)
# print arguments
sct.printv('\nCheck parameters:', verbose)
sct.printv('.. Data: ' + fname_data, verbose)
sct.printv('.. Landmarks: ' + fname_landmarks, verbose)
sct.printv('.. Segmentation: ' + fname_seg, verbose)
sct.printv('.. Path template: ' + path_template, verbose)
sct.printv('.. Output type: ' + str(output_type), verbose)
sct.printv('.. Remove temp files: ' + str(remove_temp_files), verbose)
sct.printv('\nParameters for registration:')
for pStep in range(1, len(paramreg.steps) + 1):
sct.printv('Step #' + paramreg.steps[str(pStep)].step, verbose)
sct.printv('.. Type #' + paramreg.steps[str(pStep)].type, verbose)
sct.printv(
'.. Algorithm................ ' + paramreg.steps[str(pStep)].algo,
verbose)
sct.printv(
'.. Metric................... ' +
paramreg.steps[str(pStep)].metric, verbose)
sct.printv(
'.. Number of iterations..... ' + paramreg.steps[str(pStep)].iter,
verbose)
sct.printv(
'.. Shrink factor............ ' +
paramreg.steps[str(pStep)].shrink, verbose)
sct.printv(
'.. Smoothing factor......... ' +
paramreg.steps[str(pStep)].smooth, verbose)
sct.printv(
'.. Gradient step............ ' +
paramreg.steps[str(pStep)].gradStep, verbose)
sct.printv(
'.. Degree of polynomial..... ' + paramreg.steps[str(pStep)].poly,
verbose)
path_data, file_data, ext_data = sct.extract_fname(fname_data)
sct.printv('\nCheck input labels...')
# check if label image contains coherent labels
image_label = Image(fname_landmarks)
# -> all labels must be different
labels = image_label.getNonZeroCoordinates(sorting='value')
hasDifferentLabels = True
for lab in labels:
for otherlabel in labels:
if lab != otherlabel and lab.hasEqualValue(otherlabel):
hasDifferentLabels = False
break
if not hasDifferentLabels:
sct.printv(
'ERROR: Wrong landmarks input. All labels must be different.',
verbose, 'error')
# all labels must be available in tempalte
image_label_template = Image(fname_template_label)
labels_template = image_label_template.getNonZeroCoordinates(
sorting='value')
if labels[-1].value > labels_template[-1].value:
sct.printv(
'ERROR: Wrong landmarks input. Labels must have correspondance in tempalte space. \nLabel max '
'provided: ' + str(labels[-1].value) +
'\nLabel max from template: ' + str(labels_template[-1].value),
verbose, 'error')
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = 'tmp.' + time.strftime("%y%m%d%H%M%S")
status, output = sct.run('mkdir ' + path_tmp)
# copy files to temporary folder
sct.printv('\nCopy files...', verbose)
sct.run('isct_c3d ' + fname_data + ' -o ' + path_tmp + '/data.nii')
sct.run('isct_c3d ' + fname_landmarks + ' -o ' + path_tmp +
'/landmarks.nii.gz')
sct.run('isct_c3d ' + fname_seg + ' -o ' + path_tmp +
'/segmentation.nii.gz')
sct.run('isct_c3d ' + fname_template + ' -o ' + path_tmp + '/template.nii')
sct.run('isct_c3d ' + fname_template_label + ' -o ' + path_tmp +
'/template_labels.nii.gz')
sct.run('isct_c3d ' + fname_template_seg + ' -o ' + path_tmp +
'/template_seg.nii.gz')
# go to tmp folder
os.chdir(path_tmp)
# resample data to 1mm isotropic
sct.printv('\nResample data to 1mm isotropic...', verbose)
sct.run(
'isct_c3d data.nii -resample-mm 1.0x1.0x1.0mm -interpolation Linear -o datar.nii'
)
sct.run(
'isct_c3d segmentation.nii.gz -resample-mm 1.0x1.0x1.0mm -interpolation NearestNeighbor -o segmentationr.nii.gz'
)
# N.B. resampling of labels is more complicated, because they are single-point labels, therefore resampling with neighrest neighbour can make them disappear. Therefore a more clever approach is required.
resample_labels('landmarks.nii.gz', 'datar.nii', 'landmarksr.nii.gz')
# # TODO
# sct.run('sct_label_utils -i datar.nii -t create -x 124,186,19,2:129,98,23,8 -o landmarksr.nii.gz')
# Change orientation of input images to RPI
sct.printv('\nChange orientation of input images to RPI...', verbose)
set_orientation('datar.nii', 'RPI', 'data_rpi.nii')
set_orientation('landmarksr.nii.gz', 'RPI', 'landmarks_rpi.nii.gz')
set_orientation('segmentationr.nii.gz', 'RPI', 'segmentation_rpi.nii.gz')
# # Change orientation of input images to RPI
# sct.printv('\nChange orientation of input images to RPI...', verbose)
# set_orientation('data.nii', 'RPI', 'data_rpi.nii')
# set_orientation('landmarks.nii.gz', 'RPI', 'landmarks_rpi.nii.gz')
# set_orientation('segmentation.nii.gz', 'RPI', 'segmentation_rpi.nii.gz')
# get landmarks in native space
# crop segmentation
# output: segmentation_rpi_crop.nii.gz
sct.run(
'sct_crop_image -i segmentation_rpi.nii.gz -o segmentation_rpi_crop.nii.gz -dim 2 -bzmax'
)
# straighten segmentation
sct.printv('\nStraighten the spinal cord using centerline/segmentation...',
verbose)
sct.run(
'sct_straighten_spinalcord -i segmentation_rpi_crop.nii.gz -c segmentation_rpi_crop.nii.gz -r 0 -v '
+ str(verbose), verbose)
# re-define warping field using non-cropped space (to avoid issue #367)
sct.run(
'sct_concat_transfo -w warp_straight2curve.nii.gz -d data_rpi.nii -o warp_straight2curve.nii.gz'
)
# Label preparation:
# --------------------------------------------------------------------------------
# Remove unused label on template. Keep only label present in the input label image
sct.printv(
'\nRemove unused label on template. Keep only label present in the input label image...',
verbose)
sct.run(
'sct_label_utils -t remove -i template_labels.nii.gz -o template_label.nii.gz -r landmarks_rpi.nii.gz'
)
# Make sure landmarks are INT
sct.printv('\nConvert landmarks to INT...', verbose)
sct.run(
'isct_c3d template_label.nii.gz -type int -o template_label.nii.gz',
verbose)
# Create a cross for the template labels - 5 mm
sct.printv('\nCreate a 5 mm cross for the template labels...', verbose)
sct.run(
'sct_label_utils -t cross -i template_label.nii.gz -o template_label_cross.nii.gz -c 5'
)
# Create a cross for the input labels and dilate for straightening preparation - 5 mm
sct.printv(
'\nCreate a 5mm cross for the input labels and dilate for straightening preparation...',
verbose)
sct.run(
'sct_label_utils -t cross -i landmarks_rpi.nii.gz -o landmarks_rpi_cross3x3.nii.gz -c 5 -d'
)
# Apply straightening to labels
sct.printv('\nApply straightening to labels...', verbose)
sct.run(
'sct_apply_transfo -i landmarks_rpi_cross3x3.nii.gz -o landmarks_rpi_cross3x3_straight.nii.gz -d segmentation_rpi_crop_straight.nii.gz -w warp_curve2straight.nii.gz -x nn'
)
# Convert landmarks from FLOAT32 to INT
sct.printv('\nConvert landmarks from FLOAT32 to INT...', verbose)
sct.run(
'isct_c3d landmarks_rpi_cross3x3_straight.nii.gz -type int -o landmarks_rpi_cross3x3_straight.nii.gz'
)
# Remove labels that do not correspond with each others.
sct.printv('\nRemove labels that do not correspond with each others.',
verbose)
sct.run(
'sct_label_utils -t remove-symm -i landmarks_rpi_cross3x3_straight.nii.gz -o landmarks_rpi_cross3x3_straight.nii.gz,template_label_cross.nii.gz -r template_label_cross.nii.gz'
)
# Estimate affine transfo: straight --> template (landmark-based)'
sct.printv(
'\nEstimate affine transfo: straight anat --> template (landmark-based)...',
verbose)
# converting landmarks straight and curved to physical coordinates
image_straight = Image('landmarks_rpi_cross3x3_straight.nii.gz')
landmark_straight = image_straight.getNonZeroCoordinates(sorting='value')
image_template = Image('template_label_cross.nii.gz')
landmark_template = image_template.getNonZeroCoordinates(sorting='value')
# Reorganize landmarks
points_fixed, points_moving = [], []
landmark_straight_mean = []
for coord in landmark_straight:
if coord.value not in [c.value for c in landmark_straight_mean]:
temp_landmark = coord
temp_number = 1
for other_coord in landmark_straight:
if coord.hasEqualValue(other_coord) and coord != other_coord:
temp_landmark += other_coord
temp_number += 1
landmark_straight_mean.append(temp_landmark / temp_number)
for coord in landmark_straight_mean:
point_straight = image_straight.transfo_pix2phys(
[[coord.x, coord.y, coord.z]])
points_moving.append(
[point_straight[0][0], point_straight[0][1], point_straight[0][2]])
for coord in landmark_template:
point_template = image_template.transfo_pix2phys(
[[coord.x, coord.y, coord.z]])
points_fixed.append(
[point_template[0][0], point_template[0][1], point_template[0][2]])
# Register curved landmarks on straight landmarks based on python implementation
sct.printv(
'\nComputing rigid transformation (algo=translation-scaling-z) ...',
verbose)
import msct_register_landmarks
(rotation_matrix, translation_array, points_moving_reg, points_moving_barycenter) = \
msct_register_landmarks.getRigidTransformFromLandmarks(
points_fixed, points_moving, constraints='translation-scaling-z', show=False)
# writing rigid transformation file
text_file = open("straight2templateAffine.txt", "w")
text_file.write("#Insight Transform File V1.0\n")
text_file.write("#Transform 0\n")
text_file.write(
"Transform: FixedCenterOfRotationAffineTransform_double_3_3\n")
text_file.write(
"Parameters: %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f %.9f\n"
% (1.0 / rotation_matrix[0, 0], rotation_matrix[0, 1],
rotation_matrix[0, 2], rotation_matrix[1, 0],
1.0 / rotation_matrix[1, 1], rotation_matrix[1, 2],
rotation_matrix[2, 0], rotation_matrix[2, 1],
1.0 / rotation_matrix[2, 2], translation_array[0, 0],
translation_array[0, 1], -translation_array[0, 2]))
text_file.write("FixedParameters: %.9f %.9f %.9f\n" %
(points_moving_barycenter[0], points_moving_barycenter[1],
points_moving_barycenter[2]))
text_file.close()
# Apply affine transformation: straight --> template
sct.printv('\nApply affine transformation: straight --> template...',
verbose)
sct.run(
'sct_concat_transfo -w warp_curve2straight.nii.gz,straight2templateAffine.txt -d template.nii -o warp_curve2straightAffine.nii.gz'
)
sct.run(
'sct_apply_transfo -i data_rpi.nii -o data_rpi_straight2templateAffine.nii -d template.nii -w warp_curve2straightAffine.nii.gz'
)
sct.run(
'sct_apply_transfo -i segmentation_rpi.nii.gz -o segmentation_rpi_straight2templateAffine.nii.gz -d template.nii -w warp_curve2straightAffine.nii.gz -x linear'
)
# threshold to 0.5
nii = Image('segmentation_rpi_straight2templateAffine.nii.gz')
data = nii.data
data[data < 0.5] = 0
nii.data = data
nii.setFileName('segmentation_rpi_straight2templateAffine_th.nii.gz')
nii.save()
# find min-max of anat2template (for subsequent cropping)
zmin_template, zmax_template = find_zmin_zmax(
'segmentation_rpi_straight2templateAffine_th.nii.gz')
# crop template in z-direction (for faster processing)
sct.printv('\nCrop data in template space (for faster processing)...',
verbose)
sct.run(
'sct_crop_image -i template.nii -o template_crop.nii -dim 2 -start ' +
str(zmin_template) + ' -end ' + str(zmax_template))
sct.run(
'sct_crop_image -i template_seg.nii.gz -o template_seg_crop.nii.gz -dim 2 -start '
+ str(zmin_template) + ' -end ' + str(zmax_template))
sct.run(
'sct_crop_image -i data_rpi_straight2templateAffine.nii -o data_rpi_straight2templateAffine_crop.nii -dim 2 -start '
+ str(zmin_template) + ' -end ' + str(zmax_template))
sct.run(
'sct_crop_image -i segmentation_rpi_straight2templateAffine.nii.gz -o segmentation_rpi_straight2templateAffine_crop.nii.gz -dim 2 -start '
+ str(zmin_template) + ' -end ' + str(zmax_template))
# sub-sample in z-direction
sct.printv('\nSub-sample in z-direction (for faster processing)...',
verbose)
sct.run(
'sct_resample -i template_crop.nii -o template_crop_r.nii -f 1x1x' +
zsubsample, verbose)
sct.run(
'sct_resample -i template_seg_crop.nii.gz -o template_seg_crop_r.nii.gz -f 1x1x'
+ zsubsample, verbose)
sct.run(
'sct_resample -i data_rpi_straight2templateAffine_crop.nii -o data_rpi_straight2templateAffine_crop_r.nii -f 1x1x'
+ zsubsample, verbose)
sct.run(
'sct_resample -i segmentation_rpi_straight2templateAffine_crop.nii.gz -o segmentation_rpi_straight2templateAffine_crop_r.nii.gz -f 1x1x'
+ zsubsample, verbose)
# Registration straight spinal cord to template
sct.printv('\nRegister straight spinal cord to template...', verbose)
# loop across registration steps
warp_forward = []
warp_inverse = []
for i_step in range(1, len(paramreg.steps) + 1):
sct.printv(
'\nEstimate transformation for step #' + str(i_step) + '...',
verbose)
# identify which is the src and dest
if paramreg.steps[str(i_step)].type == 'im':
src = 'data_rpi_straight2templateAffine_crop_r.nii'
dest = 'template_crop_r.nii'
interp_step = 'linear'
elif paramreg.steps[str(i_step)].type == 'seg':
src = 'segmentation_rpi_straight2templateAffine_crop_r.nii.gz'
dest = 'template_seg_crop_r.nii.gz'
interp_step = 'nn'
else:
sct.printv('ERROR: Wrong image type.', 1, 'error')
# if step>1, apply warp_forward_concat to the src image to be used
if i_step > 1:
# sct.run('sct_apply_transfo -i '+src+' -d '+dest+' -w '+','.join(warp_forward)+' -o '+sct.add_suffix(src, '_reg')+' -x '+interp_step, verbose)
sct.run(
'sct_apply_transfo -i ' + src + ' -d ' + dest + ' -w ' +
','.join(warp_forward) + ' -o ' + sct.add_suffix(src, '_reg') +
' -x ' + interp_step, verbose)
src = sct.add_suffix(src, '_reg')
# register src --> dest
warp_forward_out, warp_inverse_out = register(src, dest, paramreg,
param, str(i_step))
warp_forward.append(warp_forward_out)
warp_inverse.append(warp_inverse_out)
# Concatenate transformations:
sct.printv('\nConcatenate transformations: anat --> template...', verbose)
sct.run(
'sct_concat_transfo -w warp_curve2straightAffine.nii.gz,' +
','.join(warp_forward) +
' -d template.nii -o warp_anat2template.nii.gz', verbose)
# sct.run('sct_concat_transfo -w warp_curve2straight.nii.gz,straight2templateAffine.txt,'+','.join(warp_forward)+' -d template.nii -o warp_anat2template.nii.gz', verbose)
warp_inverse.reverse()
sct.run(
'sct_concat_transfo -w ' + ','.join(warp_inverse) +
',-straight2templateAffine.txt,warp_straight2curve.nii.gz -d data.nii -o warp_template2anat.nii.gz',
verbose)
# Apply warping fields to anat and template
if output_type == 1:
sct.run(
'sct_apply_transfo -i template.nii -o template2anat.nii.gz -d data.nii -w warp_template2anat.nii.gz -c 1',
verbose)
sct.run(
'sct_apply_transfo -i data.nii -o anat2template.nii.gz -d template.nii -w warp_anat2template.nii.gz -c 1',
verbose)
# come back to parent folder
os.chdir('..')
# Generate output files
sct.printv('\nGenerate output files...', verbose)
sct.generate_output_file(path_tmp + '/warp_template2anat.nii.gz',
'warp_template2anat.nii.gz', verbose)
sct.generate_output_file(path_tmp + '/warp_anat2template.nii.gz',
'warp_anat2template.nii.gz', verbose)
if output_type == 1:
sct.generate_output_file(path_tmp + '/template2anat.nii.gz',
'template2anat' + ext_data, verbose)
sct.generate_output_file(path_tmp + '/anat2template.nii.gz',
'anat2template' + ext_data, verbose)
# Delete temporary files
if remove_temp_files:
sct.printv('\nDelete temporary files...', verbose)
sct.run('rm -rf ' + path_tmp)
# display elapsed time
elapsed_time = time.time() - start_time
sct.printv(
'\nFinished! Elapsed time: ' + str(int(round(elapsed_time))) + 's',
verbose)
# to view results
sct.printv('\nTo view results, type:', verbose)
sct.printv('fslview ' + fname_data + ' template2anat -b 0,4000 &', verbose,
'info')
sct.printv('fslview ' + fname_template + ' -b 0,5000 anat2template &\n',
verbose, 'info')
