def main(): time_start = ph.start_timing() np.set_printoptions(precision=3) input_parser = InputArgparser( description="Register an obtained reconstruction (moving) " "to a template image/space (fixed) using rigid registration. " "The resulting registration can optionally be applied to previously " "obtained motion correction slice transforms so that a volumetric " "reconstruction is possible in the (standard anatomical) space " "defined by the fixed.", ) input_parser.add_fixed(required=True) input_parser.add_moving(required=True) input_parser.add_output(help="Path to registration transform (.txt)", required=True) input_parser.add_fixed_mask(required=False) input_parser.add_moving_mask(required=False) input_parser.add_option( option_string="--initial-transform", type=str, help="Path to initial transform. " "If not provided, registration will be initialized based on " "rigid alignment of eigenbasis of the fixed/moving image masks " "using principal component analysis", default=None) input_parser.add_v2v_method( option_string="--method", help="Registration method used for the registration.", default="RegAladin", ) input_parser.add_argument( "--refine-pca", "-refine-pca", action='store_true', help="If given, PCA-based initializations will be refined using " "RegAladin registrations.") input_parser.add_dir_input_mc() input_parser.add_verbose(default=0) input_parser.add_log_config(default=1) args = input_parser.parse_args() input_parser.print_arguments(args) if args.log_config: input_parser.log_config(os.path.abspath(__file__)) if not args.output.endswith(".txt"): raise IOError("output transformation path must end in '.txt'") dir_output = os.path.dirname(args.output) ph.create_directory(dir_output) # --------------------------------Read Data-------------------------------- ph.print_title("Read Data") fixed = st.Stack.from_filename(file_path=args.fixed, file_path_mask=args.fixed_mask, extract_slices=False) moving = st.Stack.from_filename(file_path=args.moving, file_path_mask=args.moving_mask, extract_slices=False) path_to_tmp_output = os.path.join( DIR_TMP, ph.append_to_filename(os.path.basename(args.moving), "_warped")) # ---------------------------- Initialization ---------------------------- if args.initial_transform is None: ph.print_title("Estimate initial transform using PCA") if args.moving_mask is None or args.fixed_mask is None: ph.print_warning("Fixed and moving masks are strongly recommended") transform_initializer = tinit.TransformInitializer( fixed=fixed, moving=moving, similarity_measure="NMI", refine_pca_initializations=args.refine_pca, ) transform_initializer.run() transform_init_sitk = transform_initializer.get_transform_sitk() else: transform_init_sitk = sitkh.read_transform_sitk(args.initial_transform) sitk.WriteTransform(transform_init_sitk, args.output) # -------------------Register Reconstruction to Template------------------- ph.print_title("Registration") if args.method == "RegAladin": path_to_transform_regaladin = os.path.join(DIR_TMP, "transform_regaladin.txt") # Convert SimpleITK to RegAladin transform cmd = "simplereg_transform -sitk2nreg %s %s" % ( args.output, path_to_transform_regaladin) ph.execute_command(cmd, verbose=False) # Run NiftyReg cmd_args = ["reg_aladin"] cmd_args.append("-ref '%s'" % args.fixed) cmd_args.append("-flo '%s'" % args.moving) cmd_args.append("-res '%s'" % path_to_tmp_output) cmd_args.append("-inaff '%s'" % path_to_transform_regaladin) cmd_args.append("-aff '%s'" % path_to_transform_regaladin) cmd_args.append("-rigOnly") cmd_args.append("-ln 2") # seems to perform better for spina bifida cmd_args.append("-voff") if args.fixed_mask is not None: cmd_args.append("-rmask '%s'" % args.fixed_mask) # To avoid error "0 correspondences between blocks were found" that can # occur for some cases. Also, disable moving mask, as this would be ignored # anyway cmd_args.append("-noSym") # if args.moving_mask is not None: # cmd_args.append("-fmask '%s'" % args.moving_mask) ph.print_info("Run Registration (RegAladin) ... ", newline=False) ph.execute_command(" ".join(cmd_args), verbose=False) print("done") # Convert RegAladin to SimpleITK transform cmd = "simplereg_transform -nreg2sitk '%s' '%s'" % ( path_to_transform_regaladin, args.output) ph.execute_command(cmd, verbose=False) else: path_to_transform_flirt = os.path.join(DIR_TMP, "transform_flirt.txt") # Convert SimpleITK into FLIRT transform cmd = "simplereg_transform -sitk2flirt '%s' '%s' '%s' '%s'" % ( args.output, args.fixed, args.moving, path_to_transform_flirt) ph.execute_command(cmd, verbose=False) # Define search angle ranges for FLIRT in all three dimensions search_angles = [ "-searchr%s -%d %d" % (x, 180, 180) for x in ["x", "y", "z"] ] cmd_args = ["flirt"] cmd_args.append("-in '%s'" % args.moving) cmd_args.append("-ref '%s'" % args.fixed) if args.initial_transform is not None: cmd_args.append("-init '%s'" % path_to_transform_flirt) cmd_args.append("-omat '%s'" % path_to_transform_flirt) cmd_args.append("-out '%s'" % path_to_tmp_output) cmd_args.append("-dof 6") cmd_args.append((" ").join(search_angles)) if args.moving_mask is not None: cmd_args.append("-inweight '%s'" % args.moving_mask) if args.fixed_mask is not None: cmd_args.append("-refweight '%s'" % args.fixed_mask) ph.print_info("Run Registration (FLIRT) ... ", newline=False) ph.execute_command(" ".join(cmd_args), verbose=False) print("done") # Convert FLIRT to SimpleITK transform cmd = "simplereg_transform -flirt2sitk '%s' '%s' '%s' '%s'" % ( path_to_transform_flirt, args.fixed, args.moving, args.output) ph.execute_command(cmd, verbose=False) if args.dir_input_mc is not None: ph.print_title("Update Motion-Correction Transformations") transform_sitk = sitkh.read_transform_sitk(args.output, inverse=1) if args.dir_input_mc.endswith("/"): subdir_mc = args.dir_input_mc.split("/")[-2] else: subdir_mc = args.dir_input_mc.split("/")[-1] dir_output_mc = os.path.join(dir_output, subdir_mc) ph.create_directory(dir_output_mc, delete_files=True) pattern = REGEX_FILENAMES + "[.]tfm" p = re.compile(pattern) trafos = [t for t in os.listdir(args.dir_input_mc) if p.match(t)] for t in trafos: path_to_input_transform = os.path.join(args.dir_input_mc, t) path_to_output_transform = os.path.join(dir_output_mc, t) t_sitk = sitkh.read_transform_sitk(path_to_input_transform) t_sitk = sitkh.get_composite_sitk_affine_transform( transform_sitk, t_sitk) sitk.WriteTransform(t_sitk, path_to_output_transform) ph.print_info("%d transformations written to '%s'" % (len(trafos), dir_output_mc)) if args.verbose: ph.show_niftis([args.fixed, path_to_tmp_output]) elapsed_time_total = ph.stop_timing(time_start) # Summary ph.print_title("Summary") print("Computational Time: %s" % (elapsed_time_total)) return 0
def main(): time_start = ph.start_timing() np.set_printoptions(precision=3) input_parser = InputArgparser( description="Register an obtained reconstruction (moving) " "to a template image/space (fixed) using rigid registration. " "The resulting registration can optionally be applied to previously " "obtained motion correction slice transforms so that a volumetric " "reconstruction is possible in the (standard anatomical) space " "defined by the fixed.", ) input_parser.add_fixed(required=True) input_parser.add_moving(required=True) input_parser.add_output(help="Path to registration transform (.txt)", required=True) input_parser.add_fixed_mask() input_parser.add_moving_mask() input_parser.add_dir_input_mc() input_parser.add_search_angle(default=180) input_parser.add_option(option_string="--initial-transform", type=str, help="Path to initial transform.", default=None) input_parser.add_option( option_string="--test-ap-flip", type=int, help="Turn on/off functionality to run an additional registration " "after an AP-flip. Seems to be more robust to find a better " "registration outcome in general.", default=1) input_parser.add_option( option_string="--use-flirt", type=int, help="Turn on/off functionality to use FLIRT for the registration.", default=1) input_parser.add_option( option_string="--use-regaladin", type=int, help="Turn on/off functionality to use RegAladin for the " "registration.", default=1) input_parser.add_verbose(default=0) input_parser.add_log_config(default=1) args = input_parser.parse_args() input_parser.print_arguments(args) debug = 0 if args.log_config: input_parser.log_config(os.path.abspath(__file__)) if not args.use_regaladin and not args.use_flirt: raise IOError("Either RegAladin or FLIRT must be activated.") if not args.output.endswith(".txt"): raise IOError("output transformation path must end in '.txt'") dir_output = os.path.dirname(args.output) # --------------------------------Read Data-------------------------------- ph.print_title("Read Data") fixed = st.Stack.from_filename(file_path=args.fixed, file_path_mask=args.fixed_mask, extract_slices=False) moving = st.Stack.from_filename(file_path=args.moving, file_path_mask=args.moving_mask, extract_slices=False) if args.initial_transform is not None: transform_sitk = sitkh.read_transform_sitk(args.initial_transform) else: transform_sitk = sitk.AffineTransform(fixed.sitk.GetDimension()) sitk.WriteTransform(transform_sitk, args.output) path_to_tmp_output = os.path.join( DIR_TMP, ph.append_to_filename(os.path.basename(args.moving), "_warped")) # -------------------Register Reconstruction to Template------------------- ph.print_title("Register Reconstruction to Template") if args.use_flirt: path_to_transform_flirt = os.path.join(DIR_TMP, "transform_flirt.txt") # Convert SimpleITK into FLIRT transform cmd = "simplereg_transform -sitk2flirt %s %s %s %s" % ( args.output, args.fixed, args.moving, path_to_transform_flirt) ph.execute_command(cmd, verbose=False) # Define search angle ranges for FLIRT in all three dimensions search_angles = [ "-searchr%s -%d %d" % (x, args.search_angle, args.search_angle) for x in ["x", "y", "z"] ] # flt = nipype.interfaces.fsl.FLIRT() # flt.inputs.in_file = args.moving # flt.inputs.reference = args.fixed # if args.initial_transform is not None: # flt.inputs.in_matrix_file = path_to_transform_flirt # flt.inputs.out_matrix_file = path_to_transform_flirt # # flt.inputs.output_type = "NIFTI_GZ" # flt.inputs.out_file = path_to_tmp_output # flt.inputs.args = "-dof 6" # flt.inputs.args += " %s" % " ".join(search_angles) # if args.moving_mask is not None: # flt.inputs.in_weight = args.moving_mask # if args.fixed_mask is not None: # flt.inputs.ref_weight = args.fixed_mask # ph.print_info("Run Registration (FLIRT) ... ", newline=False) # flt.run() # print("done") cmd_args = ["flirt"] cmd_args.append("-in %s" % args.moving) cmd_args.append("-ref %s" % args.fixed) if args.initial_transform is not None: cmd_args.append("-init %s" % path_to_transform_flirt) cmd_args.append("-omat %s" % path_to_transform_flirt) cmd_args.append("-out %s" % path_to_tmp_output) cmd_args.append("-dof 6") cmd_args.append((" ").join(search_angles)) if args.moving_mask is not None: cmd_args.append("-inweight %s" % args.moving_mask) if args.fixed_mask is not None: cmd_args.append("-refweight %s" % args.fixed_mask) ph.print_info("Run Registration (FLIRT) ... ", newline=False) ph.execute_command(" ".join(cmd_args), verbose=False) print("done") # Convert FLIRT to SimpleITK transform cmd = "simplereg_transform -flirt2sitk %s %s %s %s" % ( path_to_transform_flirt, args.fixed, args.moving, args.output) ph.execute_command(cmd, verbose=False) if debug: ph.show_niftis([args.fixed, path_to_tmp_output]) # Additionally, use RegAladin for more accurate alignment # Rationale: FLIRT has better capture range, but RegAladin seems to # find better alignment once it is within its capture range. if args.use_regaladin: path_to_transform_regaladin = os.path.join(DIR_TMP, "transform_regaladin.txt") # Convert SimpleITK to RegAladin transform cmd = "simplereg_transform -sitk2nreg %s %s" % ( args.output, path_to_transform_regaladin) ph.execute_command(cmd, verbose=False) # nreg = nipype.interfaces.niftyreg.RegAladin() # nreg.inputs.ref_file = args.fixed # nreg.inputs.flo_file = args.moving # nreg.inputs.res_file = path_to_tmp_output # nreg.inputs.in_aff_file = path_to_transform_regaladin # nreg.inputs.aff_file = path_to_transform_regaladin # nreg.inputs.args = "-rigOnly -voff" # if args.moving_mask is not None: # nreg.inputs.fmask_file = args.moving_mask # if args.fixed_mask is not None: # nreg.inputs.rmask_file = args.fixed_mask # ph.print_info("Run Registration (RegAladin) ... ", newline=False) # nreg.run() # print("done") cmd_args = ["reg_aladin"] cmd_args.append("-ref %s" % args.fixed) cmd_args.append("-flo %s" % args.moving) cmd_args.append("-res %s" % path_to_tmp_output) if args.initial_transform is not None or args.use_flirt == 1: cmd_args.append("-inaff %s" % path_to_transform_regaladin) cmd_args.append("-aff %s" % path_to_transform_regaladin) # cmd_args.append("-cog") # cmd_args.append("-ln 2") cmd_args.append("-rigOnly") cmd_args.append("-voff") if args.moving_mask is not None: cmd_args.append("-fmask %s" % args.moving_mask) if args.fixed_mask is not None: cmd_args.append("-rmask %s" % args.fixed_mask) ph.print_info("Run Registration (RegAladin) ... ", newline=False) ph.execute_command(" ".join(cmd_args), verbose=False) print("done") # Convert RegAladin to SimpleITK transform cmd = "simplereg_transform -nreg2sitk %s %s" % ( path_to_transform_regaladin, args.output) ph.execute_command(cmd, verbose=False) if debug: ph.show_niftis([args.fixed, path_to_tmp_output]) if args.test_ap_flip: path_to_transform_flip = os.path.join(DIR_TMP, "transform_flip.txt") path_to_tmp_output_flip = os.path.join(DIR_TMP, "output_flip.nii.gz") # Get AP-flip transform transform_ap_flip_sitk = get_ap_flip_transform(args.fixed) path_to_transform_flip_regaladin = os.path.join( DIR_TMP, "transform_flip_regaladin.txt") sitk.WriteTransform(transform_ap_flip_sitk, path_to_transform_flip) # Compose current transform with AP flip transform cmd = "simplereg_transform -c %s %s %s" % ( args.output, path_to_transform_flip, path_to_transform_flip) ph.execute_command(cmd, verbose=False) # Convert SimpleITK to RegAladin transform cmd = "simplereg_transform -sitk2nreg %s %s" % ( path_to_transform_flip, path_to_transform_flip_regaladin) ph.execute_command(cmd, verbose=False) # nreg = nipype.interfaces.niftyreg.RegAladin() # nreg.inputs.ref_file = args.fixed # nreg.inputs.flo_file = args.moving # nreg.inputs.res_file = path_to_tmp_output_flip # nreg.inputs.in_aff_file = path_to_transform_flip_regaladin # nreg.inputs.aff_file = path_to_transform_flip_regaladin # nreg.inputs.args = "-rigOnly -voff" # if args.moving_mask is not None: # nreg.inputs.fmask_file = args.moving_mask # if args.fixed_mask is not None: # nreg.inputs.rmask_file = args.fixed_mask # ph.print_info("Run Registration AP-flipped (RegAladin) ... ", # newline=False) # nreg.run() # print("done") cmd_args = ["reg_aladin"] cmd_args.append("-ref %s" % args.fixed) cmd_args.append("-flo %s" % args.moving) cmd_args.append("-res %s" % path_to_tmp_output_flip) cmd_args.append("-inaff %s" % path_to_transform_flip_regaladin) cmd_args.append("-aff %s" % path_to_transform_flip_regaladin) cmd_args.append("-rigOnly") # cmd_args.append("-ln 2") cmd_args.append("-voff") if args.moving_mask is not None: cmd_args.append("-fmask %s" % args.moving_mask) if args.fixed_mask is not None: cmd_args.append("-rmask %s" % args.fixed_mask) ph.print_info("Run Registration AP-flipped (RegAladin) ... ", newline=False) ph.execute_command(" ".join(cmd_args), verbose=False) print("done") if debug: ph.show_niftis( [args.fixed, path_to_tmp_output, path_to_tmp_output_flip]) warped_moving = st.Stack.from_filename(path_to_tmp_output, extract_slices=False) warped_moving_flip = st.Stack.from_filename(path_to_tmp_output_flip, extract_slices=False) fixed = st.Stack.from_filename(args.fixed, args.fixed_mask) stacks = [warped_moving, warped_moving_flip] image_similarity_evaluator = ise.ImageSimilarityEvaluator( stacks=stacks, reference=fixed) image_similarity_evaluator.compute_similarities() similarities = image_similarity_evaluator.get_similarities() if similarities["NMI"][1] > similarities["NMI"][0]: ph.print_info("AP-flipped outcome better") # Convert RegAladin to SimpleITK transform cmd = "simplereg_transform -nreg2sitk %s %s" % ( path_to_transform_flip_regaladin, args.output) ph.execute_command(cmd, verbose=False) # Copy better outcome cmd = "cp -p %s %s" % (path_to_tmp_output_flip, path_to_tmp_output) ph.execute_command(cmd, verbose=False) else: ph.print_info("AP-flip does not improve outcome") if args.dir_input_mc is not None: transform_sitk = sitkh.read_transform_sitk(args.output, inverse=1) if args.dir_input_mc.endswith("/"): subdir_mc = args.dir_input_mc.split("/")[-2] else: subdir_mc = args.dir_input_mc.split("/")[-1] dir_output_mc = os.path.join(dir_output, subdir_mc) ph.create_directory(dir_output_mc, delete_files=True) pattern = REGEX_FILENAMES + "[.]tfm" p = re.compile(pattern) trafos = [t for t in os.listdir(args.dir_input_mc) if p.match(t)] for t in trafos: path_to_input_transform = os.path.join(args.dir_input_mc, t) path_to_output_transform = os.path.join(dir_output_mc, t) t_sitk = sitkh.read_transform_sitk(path_to_input_transform) t_sitk = sitkh.get_composite_sitk_affine_transform( transform_sitk, t_sitk) sitk.WriteTransform(t_sitk, path_to_output_transform) if args.verbose: ph.show_niftis([args.fixed, path_to_tmp_output]) elapsed_time_total = ph.stop_timing(time_start) # Summary ph.print_title("Summary") print("Computational Time: %s" % (elapsed_time_total)) return 0
def main(): time_start = ph.start_timing() # Set print options for numpy np.set_printoptions(precision=3) input_parser = InputArgparser( description="Propagate image mask using rigid registration.", ) input_parser.add_moving(required=True) input_parser.add_moving_mask(required=True) input_parser.add_fixed(required=True) input_parser.add_output(required=True) input_parser.add_v2v_method( option_string="--method", help="Registration method used for the registration (%s)." % (", or ".join(V2V_METHOD_OPTIONS)), default="RegAladin", ) input_parser.add_option( option_string="--use-moving-mask", type=int, help="Turn on/off use of moving mask to constrain the registration.", default=0, ) input_parser.add_dilation_radius(default=1) input_parser.add_verbose(default=0) input_parser.add_log_config(default=0) args = input_parser.parse_args() input_parser.print_arguments(args) if np.alltrue([not args.output.endswith(t) for t in ALLOWED_EXTENSIONS]): raise ValueError( "output filename invalid; allowed extensions are: %s" % ", ".join(ALLOWED_EXTENSIONS)) if args.method not in V2V_METHOD_OPTIONS: raise ValueError("method must be in {%s}" % (", ".join(V2V_METHOD_OPTIONS))) if args.log_config: input_parser.log_config(os.path.abspath(__file__)) stack = st.Stack.from_filename( file_path=args.fixed, extract_slices=False, ) template = st.Stack.from_filename( file_path=args.moving, file_path_mask=args.moving_mask, extract_slices=False, ) if args.method == "FLIRT": # Define search angle ranges for FLIRT in all three dimensions # search_angles = ["-searchr%s -%d %d" % # (x, args.search_angle, args.search_angle) # for x in ["x", "y", "z"]] # options = (" ").join(search_angles) # options += " -noresample" registration = regflirt.FLIRT( registration_type="Rigid", fixed=stack, moving=template, use_fixed_mask=False, use_moving_mask=args.use_moving_mask, # options=options, use_verbose=False, ) else: registration = niftyreg.RegAladin( registration_type="Rigid", fixed=stack, moving=template, use_fixed_mask=False, use_moving_mask=args.use_moving_mask, # options="-ln 2", use_verbose=False, ) try: registration.run() except RuntimeError as e: raise RuntimeError( "%s\n\n" "Have you tried running the script with '--use-moving-mask 0'?" % e) transform_sitk = registration.get_registration_transform_sitk() stack.sitk_mask = sitk.Resample(template.sitk_mask, stack.sitk_mask, transform_sitk, sitk.sitkNearestNeighbor, 0, template.sitk_mask.GetPixelIDValue()) if args.dilation_radius > 0: stack_mask_morpher = stmorph.StackMaskMorphologicalOperations.from_sitk_mask( mask_sitk=stack.sitk_mask, dilation_radius=args.dilation_radius, dilation_kernel="Ball", use_dilation_in_plane_only=True, ) stack_mask_morpher.run_dilation() stack.sitk_mask = stack_mask_morpher.get_processed_mask_sitk() dw.DataWriter.write_mask(stack.sitk_mask, args.output) elapsed_time = ph.stop_timing(time_start) if args.verbose: ph.show_nifti(args.fixed, segmentation=args.output) ph.print_title("Summary") exe_file_info = os.path.basename(os.path.abspath(__file__)).split(".")[0] print("%s | Computational Time for Segmentation Propagation: %s" % (exe_file_info, elapsed_time)) return 0
def main(): time_start = ph.start_timing() np.set_printoptions(precision=3) input_parser = InputArgparser( description="Register an obtained reconstruction (moving) " "to a template image/space (fixed) using rigid registration. " "The resulting registration can optionally be applied to previously " "obtained motion correction slice transforms so that a volumetric " "reconstruction is possible in the (standard anatomical) space " "defined by the fixed.", ) input_parser.add_fixed(required=True) input_parser.add_moving( required=True, nargs="+", help="Specify moving image to be warped to fixed space. " "If multiple images are provided, all images will be transformed " "uniformly according to the registration obtained for the first one.") input_parser.add_dir_output(required=True) input_parser.add_dir_input() input_parser.add_suffix_mask(default="_mask") input_parser.add_search_angle(default=180) input_parser.add_option( option_string="--transform-only", type=int, help="Turn on/off functionality to transform moving image(s) to fixed " "image only, i.e. no resampling to fixed image space", default=0) input_parser.add_option( option_string="--write-transform", type=int, help="Turn on/off functionality to write registration transform", default=0) input_parser.add_verbose(default=0) args = input_parser.parse_args() input_parser.print_arguments(args) use_reg_aladin_for_refinement = True # --------------------------------Read Data-------------------------------- ph.print_title("Read Data") data_reader = dr.MultipleImagesReader(args.moving, suffix_mask="_mask") data_reader.read_data() moving = data_reader.get_data() data_reader = dr.MultipleImagesReader([args.fixed], suffix_mask="_mask") data_reader.read_data() fixed = data_reader.get_data()[0] # -------------------Register Reconstruction to Template------------------- ph.print_title("Register Reconstruction to Template") # Define search angle ranges for FLIRT in all three dimensions search_angles = [ "-searchr%s -%d %d" % (x, args.search_angle, args.search_angle) for x in ["x", "y", "z"] ] search_angles = (" ").join(search_angles) options_args = [] options_args.append(search_angles) # cost = "mutualinfo" # options_args.append("-searchcost %s -cost %s" % (cost, cost)) registration = regflirt.FLIRT( fixed=moving[0], moving=fixed, # use_fixed_mask=True, # use_moving_mask=True, # moving mask only seems to work for SB cases registration_type="Rigid", use_verbose=False, options=(" ").join(options_args), ) ph.print_info("Run Registration (FLIRT) ... ", newline=False) registration.run() print("done") transform_sitk = registration.get_registration_transform_sitk() if args.write_transform: path_to_transform = os.path.join(args.dir_output, "registration_transform_sitk.txt") sitk.WriteTransform(transform_sitk, path_to_transform) # Apply rigidly transform to align reconstruction (moving) with template # (fixed) for m in moving: m.update_motion_correction(transform_sitk) # Additionally, use RegAladin for more accurate alignment # Rationale: FLIRT has better capture range, but RegAladin seems to # find better alignment once it is within its capture range. if use_reg_aladin_for_refinement: registration = niftyreg.RegAladin( fixed=m, use_fixed_mask=True, moving=fixed, registration_type="Rigid", use_verbose=False, ) ph.print_info("Run Registration (RegAladin) ... ", newline=False) registration.run() print("done") transform2_sitk = registration.get_registration_transform_sitk() m.update_motion_correction(transform2_sitk) transform_sitk = sitkh.get_composite_sitk_affine_transform( transform2_sitk, transform_sitk) if args.transform_only: for m in moving: m.write(args.dir_output, write_mask=False) ph.exit() # Resample reconstruction (moving) to template space (fixed) warped_moving = [ m.get_resampled_stack(fixed.sitk, interpolator="Linear") for m in moving ] for wm in warped_moving: wm.set_filename(wm.get_filename() + "ResamplingToTemplateSpace") if args.verbose: sitkh.show_stacks([fixed, wm], segmentation=fixed) # Write resampled reconstruction (moving) wm.write(args.dir_output, write_mask=False) if args.dir_input is not None: data_reader = dr.ImageSlicesDirectoryReader( path_to_directory=args.dir_input, suffix_mask=args.suffix_mask) data_reader.read_data() stacks = data_reader.get_data() for i, stack in enumerate(stacks): stack.update_motion_correction(transform_sitk) ph.print_info("Stack %d/%d: All slice transforms updated" % (i + 1, len(stacks))) # Write transformed slices stack.write( os.path.join(args.dir_output, "motion_correction"), write_mask=True, write_slices=True, write_transforms=True, suffix_mask=args.suffix_mask, ) elapsed_time_total = ph.stop_timing(time_start) # Summary ph.print_title("Summary") print("Computational Time: %s" % (elapsed_time_total)) return 0