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')