def apply(self):
# Initialization
fname_src = self.input_filename # source image (moving)
list_warp = self.list_warp # list of warping fields
fname_out = self.output_filename # output
fname_dest = self.fname_dest # destination image (fix)
verbose = self.verbose
remove_temp_files = self.remove_temp_files
crop_reference = self.crop # if = 1, put 0 everywhere around warping field, if = 2, real crop
interp = sct.get_interpolation('isct_antsApplyTransforms', self.interp)
# Parse list of warping fields
sct.printv('\nParse list of warping fields...', verbose)
use_inverse = []
fname_warp_list_invert = []
# list_warp = list_warp.replace(' ', '') # remove spaces
# list_warp = list_warp.split(",") # parse with comma
for idx_warp, path_warp in enumerate(self.list_warp):
# Check if this transformation should be inverted
if path_warp in self.list_warpinv:
use_inverse.append('-i')
# list_warp[idx_warp] = path_warp[1:] # remove '-'
fname_warp_list_invert += [[
use_inverse[idx_warp], list_warp[idx_warp]
]]
else:
use_inverse.append('')
fname_warp_list_invert += [[path_warp]]
path_warp = list_warp[idx_warp]
if path_warp.endswith((".nii", ".nii.gz")) \
and msct_image.Image(list_warp[idx_warp]).header.get_intent()[0] != 'vector':
raise ValueError("Displacement field in {} is invalid: should be encoded" \
" in a 5D file with vector intent code" \
" (see https://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h" \
.format(path_warp))
# need to check if last warping field is an affine transfo
isLastAffine = False
path_fname, file_fname, ext_fname = sct.extract_fname(
fname_warp_list_invert[-1][-1])
if ext_fname in ['.txt', '.mat']:
isLastAffine = True
# check if destination file is 3d
if not sct.check_if_3d(fname_dest):
sct.printv('ERROR: Destination data must be 3d')
# N.B. Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order
fname_warp_list_invert.reverse()
fname_warp_list_invert = functools.reduce(lambda x, y: x + y,
fname_warp_list_invert)
# 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)
# Get output folder and file name
if fname_out == '':
path_out = '' # output in user's current directory
file_out = file_src + '_reg'
ext_out = ext_src
fname_out = os.path.join(path_out, file_out + ext_out)
# Get dimensions of data
sct.printv('\nGet dimensions of data...', verbose)
img_src = msct_image.Image(fname_src)
nx, ny, nz, nt, px, py, pz, pt = img_src.dim
# nx, ny, nz, nt, px, py, pz, pt = sct.get_dimension(fname_src)
sct.printv(
' ' + str(nx) + ' x ' + str(ny) + ' x ' + str(nz) + ' x ' +
str(nt), verbose)
# if 3d
if nt == 1:
# Apply transformation
sct.printv('\nApply transformation...', verbose)
if nz in [0, 1]:
dim = '2'
else:
dim = '3'
sct.run([
'isct_antsApplyTransforms', '-d', dim, '-i', fname_src, '-o',
fname_out, '-t'
] + fname_warp_list_invert + ['-r', fname_dest] + interp,
verbose=verbose,
is_sct_binary=True)
# if 4d, loop across the T dimension
else:
path_tmp = sct.tmp_create(basename="apply_transfo",
verbose=verbose)
# convert to nifti into temp folder
sct.printv(
'\nCopying input data to tmp folder and convert to nii...',
verbose)
img_src.save(os.path.join(path_tmp, "data.nii"))
sct.copy(fname_dest, os.path.join(path_tmp, file_dest + ext_dest))
fname_warp_list_tmp = []
for fname_warp in list_warp:
path_warp, file_warp, ext_warp = sct.extract_fname(fname_warp)
sct.copy(fname_warp,
os.path.join(path_tmp, file_warp + ext_warp))
fname_warp_list_tmp.append(file_warp + ext_warp)
fname_warp_list_invert_tmp = fname_warp_list_tmp[::-1]
curdir = os.getcwd()
os.chdir(path_tmp)
# split along T dimension
sct.printv('\nSplit along T dimension...', verbose)
im_dat = msct_image.Image('data.nii')
im_header = im_dat.hdr
data_split_list = sct_image.split_data(im_dat, 3)
for im in data_split_list:
im.save()
# apply transfo
sct.printv('\nApply transformation to each 3D volume...', verbose)
for it in range(nt):
file_data_split = 'data_T' + str(it).zfill(4) + '.nii'
file_data_split_reg = 'data_reg_T' + str(it).zfill(4) + '.nii'
status, output = sct.run([
'isct_antsApplyTransforms',
'-d',
'3',
'-i',
file_data_split,
'-o',
file_data_split_reg,
'-t',
] + fname_warp_list_invert_tmp + [
'-r',
file_dest + ext_dest,
] + interp,
verbose,
is_sct_binary=True)
# Merge files back
sct.printv('\nMerge file back...', verbose)
import glob
path_out, name_out, ext_out = sct.extract_fname(fname_out)
# im_list = [Image(file_name) for file_name in glob.glob('data_reg_T*.nii')]
# concat_data use to take a list of image in input, now takes a list of file names to open the files one by one (see issue #715)
fname_list = glob.glob('data_reg_T*.nii')
fname_list.sort()
im_out = sct_image.concat_data(fname_list, 3, im_header['pixdim'])
im_out.save(name_out + ext_out)
os.chdir(curdir)
sct.generate_output_file(
os.path.join(path_tmp, name_out + ext_out), fname_out)
# Delete temporary folder if specified
if int(remove_temp_files):
sct.printv('\nRemove temporary files...', verbose)
sct.rmtree(path_tmp, verbose=verbose)
# 2. crop the resulting image using dimensions from the warping field
warping_field = fname_warp_list_invert[-1]
# if last warping field is an affine transfo, we need to compute the space of the concatenate warping field:
if isLastAffine:
sct.printv(
'WARNING: the resulting image could have wrong apparent results. You should use an affine transformation as last transformation...',
verbose, 'warning')
elif crop_reference == 1:
ImageCropper(input_file=fname_out,
output_file=fname_out,
ref=warping_field,
background=0).crop()
# sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field+' -b 0')
elif crop_reference == 2:
ImageCropper(input_file=fname_out,
output_file=fname_out,
ref=warping_field).crop()
# sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field)
sct.display_viewer_syntax([fname_dest, fname_out], verbose=verbose)
def main(args=None):
if args is None:
args = sys.argv[1:]
# initialize parameters
param = Param()
# Initialization
fname_output = ''
path_out = ''
fname_src_seg = ''
fname_dest_seg = ''
fname_src_label = ''
fname_dest_label = ''
generate_warpinv = 1
start_time = time.time()
# get path of the toolbox
path_sct = os.environ.get("SCT_DIR",
os.path.dirname(os.path.dirname(__file__)))
# 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',
slicewise='0',
dof='Tx_Ty_Tz_Rx_Ry_Rz') # only used to put src into dest space
step1 = Paramreg(step='1', type='im')
paramreg = ParamregMultiStep([step0, step1])
parser = get_parser(paramreg=paramreg)
arguments = parser.parse(args)
# 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 '-ilabel' in arguments:
fname_src_label = arguments['-ilabel']
if '-dlabel' in arguments:
fname_dest_label = arguments['-dlabel']
if '-o' in arguments:
fname_output = arguments['-o']
if '-ofolder' in arguments:
path_out = arguments['-ofolder']
if '-owarp' in arguments:
fname_output_warp = arguments['-owarp']
else:
fname_output_warp = ''
if '-initwarp' in arguments:
fname_initwarp = os.path.abspath(arguments['-initwarp'])
else:
fname_initwarp = ''
if '-initwarpinv' in arguments:
fname_initwarpinv = os.path.abspath(arguments['-initwarpinv'])
else:
fname_initwarpinv = ''
if '-m' in arguments:
fname_mask = arguments['-m']
else:
fname_mask = ''
padding = arguments['-z']
if "-param" in arguments:
paramreg_user = arguments['-param']
# update registration parameters
for paramStep in paramreg_user:
paramreg.addStep(paramStep)
path_qc = arguments.get("-qc", None)
identity = int(arguments['-identity'])
interp = arguments['-x']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
# sct.printv(arguments)
sct.printv('\nInput parameters:')
sct.printv(' Source .............. ' + fname_src)
sct.printv(' Destination ......... ' + fname_dest)
sct.printv(' Init transfo ........ ' + fname_initwarp)
sct.printv(' Mask ................ ' + fname_mask)
sct.printv(' Output name ......... ' + fname_output)
# sct.printv(' Algorithm ........... '+paramreg.algo)
# sct.printv(' Number of iterations '+paramreg.iter)
# sct.printv(' Metric .............. '+paramreg.metric)
sct.printv(' Remove temp files ... ' + str(remove_temp_files))
sct.printv(' 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 user selected type=seg, but did not input segmentation data
if 'paramreg_user' in locals():
if True in [
'type=seg' in paramreg_user[i]
for i in range(len(paramreg_user))
]:
if fname_src_seg == '' or fname_dest_seg == '':
sct.printv(
'\nERROR: if you select type=seg you must specify -iseg and -dseg flags.\n',
1, 'error')
# 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)
# check if source and destination images have the same name (related to issue #373)
# If so, change names to avoid conflict of result files and warns the user
suffix_src, suffix_dest = '_reg', '_reg'
if file_src == file_dest:
suffix_src, suffix_dest = '_src_reg', '_dest_reg'
# define output folder and file name
if fname_output == '':
path_out = '' if not path_out else path_out # output in user's current directory
file_out = file_src + suffix_src
file_out_inv = file_dest + suffix_dest
ext_out = ext_src
else:
path, file_out, ext_out = sct.extract_fname(fname_output)
path_out = path if not path_out else path_out
file_out_inv = file_out + '_inv'
# create temporary folder
path_tmp = sct.tmp_create()
sct.printv('\nCopying input data to tmp folder and convert to nii...',
verbose)
Image(fname_src).save(os.path.join(path_tmp, "src.nii"))
Image(fname_dest).save(os.path.join(path_tmp, "dest.nii"))
if fname_src_seg:
Image(fname_src_seg).save(os.path.join(path_tmp, "src_seg.nii"))
if fname_dest_seg:
Image(fname_dest_seg).save(os.path.join(path_tmp, "dest_seg.nii"))
if fname_src_label:
Image(fname_src_label).save(os.path.join(path_tmp, "src_label.nii"))
Image(fname_dest_label).save(os.path.join(path_tmp, "dest_label.nii"))
if fname_mask != '':
Image(fname_mask).save(os.path.join(path_tmp, "mask.nii.gz"))
# go to tmp folder
curdir = os.getcwd()
os.chdir(path_tmp)
# reorient destination to RPI
Image('dest.nii').change_orientation("RPI").save('dest_RPI.nii')
if fname_dest_seg:
Image('dest_seg.nii').change_orientation("RPI").save(
'dest_seg_RPI.nii')
if fname_dest_label:
Image('dest_label.nii').change_orientation("RPI").save(
'dest_label_RPI.nii')
if identity:
# overwrite paramreg and only do one identity transformation
step0 = Paramreg(step='0',
type='im',
algo='syn',
metric='MI',
iter='0',
shrink='1',
smooth='0',
gradStep='0.5')
paramreg = ParamregMultiStep([step0])
# Put source into destination space using header (no estimation -- purely based on header)
# 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
# initialize list of warping fields
warp_forward = []
warp_inverse = []
# initial warping is specified, update list of warping fields and skip step=0
if fname_initwarp:
sct.printv('\nSkip step=0 and replace with initial transformations: ',
param.verbose)
sct.printv(' ' + fname_initwarp, param.verbose)
# sct.copy(fname_initwarp, 'warp_forward_0.nii.gz')
warp_forward = [fname_initwarp]
start_step = 1
if fname_initwarpinv:
warp_inverse = [fname_initwarpinv]
else:
sct.printv(
'\nWARNING: No initial inverse warping field was specified, therefore the inverse warping field '
'will NOT be generated.', param.verbose, 'warning')
generate_warpinv = 0
else:
start_step = 0
# loop across registration steps
for i_step in range(start_step, len(paramreg.steps)):
sct.printv('\n--\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_RPI.nii'
interp_step = 'spline'
elif paramreg.steps[str(i_step)].type == 'seg':
src = 'src_seg.nii'
dest = 'dest_seg_RPI.nii'
interp_step = 'nn'
elif paramreg.steps[str(i_step)].type == 'label':
src = 'src_label.nii'
dest = 'dest_label_RPI.nii'
interp_step = 'nn'
else:
# src = dest = interp_step = None
sct.printv('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.printv('\nApply transformation from previous step',
param.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.insert(0, 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)
sct.run([
'sct_concat_transfo', '-w', ','.join(warp_inverse), '-d', 'src.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
os.chdir(curdir)
# Generate output files
sct.printv('\nGenerate output files...', verbose)
# generate: src_reg
fname_src2dest = sct.generate_output_file(
os.path.join(path_tmp, "src_reg.nii"),
os.path.join(path_out, file_out + ext_out), verbose)
# generate: forward warping field
if fname_output_warp == '':
fname_output_warp = os.path.join(
path_out, 'warp_' + file_src + '2' + file_dest + '.nii.gz')
sct.generate_output_file(os.path.join(path_tmp, "warp_src2dest.nii.gz"),
fname_output_warp, verbose)
if generate_warpinv:
# generate: dest_reg
fname_dest2src = sct.generate_output_file(
os.path.join(path_tmp, "dest_reg.nii"),
os.path.join(path_out, file_out_inv + ext_dest), verbose)
# generate: inverse warping field
sct.generate_output_file(
os.path.join(path_tmp, "warp_dest2src.nii.gz"),
os.path.join(path_out,
'warp_' + file_dest + '2' + file_src + '.nii.gz'),
verbose)
# Delete temporary files
if remove_temp_files:
sct.printv('\nRemove temporary files...', verbose)
sct.rmtree(path_tmp, verbose=verbose)
# display elapsed time
elapsed_time = time.time() - start_time
sct.printv(
'\nFinished! Elapsed time: ' + str(int(np.round(elapsed_time))) + 's',
verbose)
if path_qc is not None:
if fname_dest_seg:
generate_qc(fname_src2dest,
fname_in2=fname_dest,
fname_seg=fname_dest_seg,
args=args,
path_qc=os.path.abspath(path_qc),
process='sct_register_multimodal')
else:
sct.printv(
'WARNING: Cannot generate QC because it requires destination segmentation.',
1, 'warning')
if generate_warpinv:
sct.display_viewer_syntax([fname_src, fname_dest2src], verbose=verbose)
sct.display_viewer_syntax([fname_dest, fname_src2dest], verbose=verbose)
def main(args=None):
"""
Main function
:param args:
:return:
"""
# get parser args
if args is None:
args = None if sys.argv[1:] else ['--help']
else:
# flatten the list of input arguments because -w and -winv carry a nested list
lst = []
for line in args:
lst.append(line) if isinstance(line, str) else lst.extend(line)
args = lst
parser = get_parser()
arguments = parser.parse_args(args=args)
# Initialization
fname_warp_final = '' # concatenated transformations
fname_dest = arguments.d
fname_warp_list = arguments.w
warpinv_filename = arguments.winv
if arguments.o is not None:
fname_warp_final = arguments.o
verbose = arguments.v
sct.init_sct(log_level=verbose, update=True) # Update log level
# Parse list of warping fields
sct.printv('\nParse list of warping fields...', verbose)
use_inverse = []
fname_warp_list_invert = []
# list_warp = list_warp.replace(' ', '') # remove spaces
# list_warp = list_warp.split(",") # parse with comma
for idx_warp, path_warp in enumerate(fname_warp_list):
# Check if this transformation should be inverted
if path_warp in warpinv_filename:
use_inverse.append('-i')
# list_warp[idx_warp] = path_warp[1:] # remove '-'
fname_warp_list_invert += [[
use_inverse[idx_warp], fname_warp_list[idx_warp]
]]
else:
use_inverse.append('')
fname_warp_list_invert += [[path_warp]]
path_warp = fname_warp_list[idx_warp]
if path_warp.endswith((".nii", ".nii.gz")) \
and Image(fname_warp_list[idx_warp]).header.get_intent()[0] != 'vector':
raise ValueError("Displacement field in {} is invalid: should be encoded" \
" in a 5D file with vector intent code" \
" (see https://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h" \
.format(path_warp))
# need to check if last warping field is an affine transfo
isLastAffine = False
path_fname, file_fname, ext_fname = sct.extract_fname(
fname_warp_list_invert[-1][-1])
if ext_fname in ['.txt', '.mat']:
isLastAffine = True
# check if destination file is 3d
if not sct.check_if_3d(fname_dest):
sct.printv('ERROR: Destination data must be 3d')
# Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order
fname_warp_list_invert.reverse()
fname_warp_list_invert = functools.reduce(lambda x, y: x + y,
fname_warp_list_invert)
# Check file existence
sct.printv('\nCheck file existence...', verbose)
sct.check_file_exist(fname_dest, verbose)
for i in range(len(fname_warp_list)):
sct.check_file_exist(fname_warp_list[i], verbose)
# Get output folder and file name
if fname_warp_final == '':
path_out, file_out, ext_out = sct.extract_fname(param.fname_warp_final)
else:
path_out, file_out, ext_out = sct.extract_fname(fname_warp_final)
# Check dimension of destination data (cf. issue #1419, #1429)
im_dest = Image(fname_dest)
if im_dest.dim[2] == 1:
dimensionality = '2'
else:
dimensionality = '3'
cmd = [
'isct_ComposeMultiTransform', dimensionality, 'warp_final' + ext_out,
'-R', fname_dest
] + fname_warp_list_invert
status, output = sct.run(cmd, verbose=verbose, is_sct_binary=True)
# check if output was generated
if not os.path.isfile('warp_final' + ext_out):
sct.printv('ERROR: Warping field was not generated.\n' + output, 1,
'error')
# Generate output files
sct.printv('\nGenerate output files...', verbose)
sct.generate_output_file('warp_final' + ext_out,
os.path.join(path_out, file_out + ext_out))
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 apply(self):
# Initialization
fname_src = self.input_filename # source image (moving)
fname_warp_list = self.warp_input # list of warping fields
fname_dest = self.output_filename # destination image (fix)
fname_src_reg = self.source_reg
verbose = self.verbose
remove_temp_files = self.remove_temp_files
fsloutput = 'export FSLOUTPUTTYPE=NIFTI; ' # for faster processing, all outputs are in NIFTI
crop_reference = self.crop # if = 1, put 0 everywhere around warping field, if = 2, real crop
# Parameters for debug mode
if self.debug:
print '\n*** WARNING: DEBUG MODE ON ***\n'
# get path of the testing data
status, path_sct_data = commands.getstatusoutput('echo $SCT_TESTING_DATA_DIR')
fname_src = path_sct_data+'/template/MNI-Poly-AMU_T2.nii.gz'
fname_warp_list = path_sct_data+'/t2/warp_template2anat.nii.gz'
fname_dest = path_sct_data+'/t2/t2.nii.gz'
verbose = 1
interp = sct.get_interpolation('isct_antsApplyTransforms', self.interp)
# Parse list of warping fields
sct.printv('\nParse list of warping fields...', verbose)
use_inverse = []
fname_warp_list_invert = []
# fname_warp_list = fname_warp_list.replace(' ', '') # remove spaces
# fname_warp_list = fname_warp_list.split(",") # parse with comma
for i in range(len(fname_warp_list)):
# Check if inverse matrix is specified with '-' at the beginning of file name
if fname_warp_list[i].find('-') == 0:
use_inverse.append('-i ')
fname_warp_list[i] = fname_warp_list[i][1:] # remove '-'
else:
use_inverse.append('')
sct.printv(' Transfo #'+str(i)+': '+use_inverse[i]+fname_warp_list[i], verbose)
fname_warp_list_invert.append(use_inverse[i]+fname_warp_list[i])
# need to check if last warping field is an affine transfo
isLastAffine = False
path_fname, file_fname, ext_fname = sct.extract_fname(fname_warp_list_invert[-1])
if ext_fname in ['.txt','.mat']:
isLastAffine = True
# Check file existence
sct.printv('\nCheck file existence...', verbose)
sct.check_file_exist(fname_src, self.verbose)
sct.check_file_exist(fname_dest, self.verbose)
for i in range(len(fname_warp_list)):
# check if file exist
sct.check_file_exist(fname_warp_list[i], self.verbose)
# check if destination file is 3d
sct.check_if_3d(fname_dest)
# N.B. Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order
fname_warp_list_invert.reverse()
# 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)
# Get output folder and file name
if fname_src_reg == '':
path_out = '' # output in user's current directory
file_out = file_src+'_reg'
ext_out = ext_src
fname_out = path_out+file_out+ext_out
else:
fname_out = fname_src_reg
# Get dimensions of data
sct.printv('\nGet dimensions of data...', verbose)
nx, ny, nz, nt, px, py, pz, pt = sct.get_dimension(fname_src)
sct.printv(' ' + str(nx) + ' x ' + str(ny) + ' x ' + str(nz)+ ' x ' + str(nt), verbose)
# if 3d
if nt == 1:
# Apply transformation
sct.printv('\nApply transformation...', verbose)
sct.run('isct_antsApplyTransforms -d 3 -i '+fname_src+' -o '+fname_out+' -t '+' '.join(fname_warp_list_invert)+' -r '+fname_dest+interp, verbose)
# if 4d, loop across the T dimension
else:
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = sct.slash_at_the_end('tmp.'+time.strftime("%y%m%d%H%M%S"), 1)
# sct.run('mkdir '+path_tmp, verbose)
sct.run('mkdir '+path_tmp, verbose)
# Copying input data to tmp folder
# NB: cannot use c3d here because c3d cannot convert 4D data.
sct.printv('\nCopying input data to tmp folder and convert to nii...', verbose)
sct.run('cp '+fname_src+' '+path_tmp+'data'+ext_src, verbose)
sct.run('cp '+fname_dest+' '+path_tmp+'dest'+ext_dest, verbose)
for i,warp in enumerate(fname_warp_list_invert):
sct.run('cp ' + warp + ' ' + path_tmp + warp, verbose)
# go to tmp folder
os.chdir(path_tmp)
try:
# convert to nii format
sct.run('fslchfiletype NIFTI data', verbose)
# split along T dimension
sct.printv('\nSplit along T dimension...', verbose)
sct.run(fsloutput+'fslsplit data data_T', verbose)
# apply transfo
sct.printv('\nApply transformation to each 3D volume...', verbose)
for it in range(nt):
file_data_split = 'data_T'+str(it).zfill(4)+'.nii'
file_data_split_reg = 'data_reg_T'+str(it).zfill(4)+'.nii'
sct.run('isct_antsApplyTransforms -d 3 -i '+file_data_split+' -o '+file_data_split_reg+' -t '+' '.join(fname_warp_list_invert)+' -r dest'+ext_dest+interp, verbose)
# Merge files back
sct.printv('\nMerge file back...', verbose)
#cmd = fsloutput+'fslmerge -t '+fname_out
cmd = 'fslmerge -t '+fname_out
for it in range(nt):
file_data_split_reg = 'data_reg_T'+str(it).zfill(4)+'.nii'
cmd = cmd+' '+file_data_split_reg
sct.run(cmd, verbose)
except Exception, e:
raise e
# Copy result to parent folder
sct.run('cp ' + fname_out + ' ../' + fname_out)
# come back to parent folder
os.chdir('..')
# Delete temporary folder if specified
if int(remove_temp_files):
sct.printv('\nRemove temporary files...', verbose)
sct.run('rm -rf '+path_tmp, verbose)
def main():
# Initialization
fname_src = '' # source image (moving)
fname_warp_list = '' # list of warping fields
fname_dest = '' # destination image (fix)
fname_src_reg = ''
verbose = 1
fsloutput = 'export FSLOUTPUTTYPE=NIFTI; ' # for faster processing, all outputs are in NIFTI
crop_reference = 0 # if = 1, put 0 everywhere around warping field, if = 2, real crop
# Parameters for debug mode
if param.debug:
print '\n*** WARNING: DEBUG MODE ON ***\n'
# get path of the testing data
status, path_sct_data = commands.getstatusoutput('echo $SCT_TESTING_DATA_DIR')
fname_src = path_sct_data+'/template/MNI-Poly-AMU_T2.nii.gz'
fname_warp_list = path_sct_data+'/t2/warp_template2anat.nii.gz'
fname_dest = path_sct_data+'/t2/t2.nii.gz'
verbose = 1
else:
# Check input parameters
try:
opts, args = getopt.getopt(sys.argv[1:], 'hi:d:o:v:w:x:c:')
except getopt.GetoptError:
usage()
if not opts:
usage()
for opt, arg in opts:
if opt == '-h':
usage()
elif opt in ('-i'):
fname_src = arg
elif opt in ('-d'):
fname_dest = arg
elif opt in ('-o'):
fname_src_reg = arg
elif opt in ('-x'):
param.interp = arg
elif opt in ('-v'):
verbose = int(arg)
elif opt in ('-w'):
fname_warp_list = arg
elif opt in ('-c'):
crop_reference = int(arg)
# display usage if a mandatory argument is not provided
if fname_src == '' or fname_warp_list == '' or fname_dest == '':
usage()
# get the right interpolation field depending on method
interp = sct.get_interpolation('isct_antsApplyTransforms', param.interp)
# Parse list of warping fields
sct.printv('\nParse list of warping fields...', verbose)
use_inverse = []
fname_warp_list_invert = []
fname_warp_list = fname_warp_list.replace(' ', '') # remove spaces
fname_warp_list = fname_warp_list.split(",") # parse with comma
for i in range(len(fname_warp_list)):
# Check if inverse matrix is specified with '-' at the beginning of file name
if fname_warp_list[i].find('-') == 0:
use_inverse.append('-i ')
fname_warp_list[i] = fname_warp_list[i][1:] # remove '-'
else:
use_inverse.append('')
sct.printv(' Transfo #'+str(i)+': '+use_inverse[i]+fname_warp_list[i], verbose)
fname_warp_list_invert.append(use_inverse[i]+fname_warp_list[i])
# need to check if last warping field is an affine transfo
isLastAffine = False
path_fname, file_fname, ext_fname = sct.extract_fname(fname_warp_list_invert[-1])
if ext_fname in ['.txt','.mat']:
isLastAffine = True
# Check file existence
sct.printv('\nCheck file existence...', verbose)
sct.check_file_exist(fname_src)
sct.check_file_exist(fname_dest)
for i in range(len(fname_warp_list)):
# check if file exist
sct.check_file_exist(fname_warp_list[i])
for i in range(len(fname_warp_list_invert)):
sct.check_file_exist(fname_warp_list_invert[i])
# check if destination file is 3d
sct.check_if_3d(fname_dest)
# N.B. Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order
fname_warp_list_invert.reverse()
# Extract path, file and extension
# path_src, file_src, ext_src = sct.extract_fname(os.path.abspath(fname_src))
# fname_dest = os.path.abspath(fname_dest)
path_src, file_src, ext_src = sct.extract_fname(fname_src)
# fname_dest = os.path.abspath(fname_dest
# Get output folder and file name
if fname_src_reg == '':
path_out = '' # output in user's current directory
file_out = file_src+'_reg'
ext_out = ext_src
fname_out = path_out+file_out+ext_out
else:
# path_out, file_out, ext_out = sct.extract_fname(fname_src_reg)
fname_out = fname_src_reg
# Get dimensions of data
sct.printv('\nGet dimensions of data...', verbose)
nx, ny, nz, nt, px, py, pz, pt = sct.get_dimension(fname_src)
sct.printv(' ' + str(nx) + ' x ' + str(ny) + ' x ' + str(nz)+ ' x ' + str(nt), verbose)
# if 3d
if nt == 1:
# Apply transformation
sct.printv('\nApply transformation...', verbose)
sct.run('isct_antsApplyTransforms -d 3 -i '+fname_src+' -o '+fname_out+' -t '+' '.join(fname_warp_list_invert)+' -r '+fname_dest+interp, verbose)
# if 4d, loop across the T dimension
else:
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = sct.slash_at_the_end('tmp.'+time.strftime("%y%m%d%H%M%S"), 1)
sct.run('mkdir '+path_tmp, verbose)
# Copying input data to tmp folder
# NB: cannot use c3d here because c3d cannot convert 4D data.
sct.printv('\nCopying input data to tmp folder and convert to nii...', verbose)
sct.run('cp '+fname_src+' '+path_tmp+'data'+ext_src, verbose)
# go to tmp folder
os.chdir(path_tmp)
# convert to nii format
sct.run('fslchfiletype NIFTI data', verbose)
# split along T dimension
sct.printv('\nSplit along T dimension...', verbose)
sct.run(fsloutput+'fslsplit data data_T', verbose)
# apply transfo
sct.printv('\nApply transformation to each 3D volume...', verbose)
for it in range(nt):
file_data_split = 'data_T'+str(it).zfill(4)+'.nii'
file_data_split_reg = 'data_reg_T'+str(it).zfill(4)+'.nii'
sct.run('isct_antsApplyTransforms -d 3 -i '+file_data_split+' -o '+file_data_split_reg+' -t '+' '.join(fname_warp_list_invert)+' -r '+fname_dest+interp, verbose)
# Merge files back
sct.printv('\nMerge file back...', verbose)
cmd = fsloutput+'fslmerge -t '+fname_out
for it in range(nt):
file_data_split_reg = 'data_reg_T'+str(it).zfill(4)+'.nii'
cmd = cmd+' '+file_data_split_reg
sct.run(cmd, param.verbose)
# come back to parent folder
os.chdir('..')
# 2. crop the resulting image using dimensions from the warping field
warping_field = fname_warp_list_invert[-1]
# if last warping field is an affine transfo, we need to compute the space of the concatenate warping field:
if isLastAffine:
sct.printv('WARNING: the resulting image could have wrong apparent results. You should use an affine transformation as last transformation...',1,'warning')
elif crop_reference == 1:
sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field+' -b 0')
elif crop_reference == 2:
sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field)
# display elapsed time
sct.printv('\nDone! To view results, type:', verbose)
sct.printv('fslview '+fname_dest+' '+fname_out+' &\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(args=None):
if args is None:
args = sys.argv[1:]
# initialize parameters
param = Param()
# Initialization
fname_output = ''
path_out = ''
fname_src_seg = ''
fname_dest_seg = ''
fname_src_label = ''
fname_dest_label = ''
generate_warpinv = 1
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', slicewise='0', dof='Tx_Ty_Tz_Rx_Ry_Rz') # only used to put src into dest space
step1 = Paramreg(step='1', type='im')
paramreg = ParamregMultiStep([step0, step1])
parser = get_parser(paramreg=paramreg)
arguments = parser.parse(args)
# 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 '-ilabel' in arguments:
fname_src_label = arguments['-ilabel']
if '-dlabel' in arguments:
fname_dest_label = arguments['-dlabel']
if '-o' in arguments:
fname_output = arguments['-o']
if '-ofolder' in arguments:
path_out = arguments['-ofolder']
if '-owarp' in arguments:
fname_output_warp = arguments['-owarp']
else:
fname_output_warp = ''
if '-initwarp' in arguments:
fname_initwarp = os.path.abspath(arguments['-initwarp'])
else:
fname_initwarp = ''
if '-initwarpinv' in arguments:
fname_initwarpinv = os.path.abspath(arguments['-initwarpinv'])
else:
fname_initwarpinv = ''
if '-m' in arguments:
fname_mask = arguments['-m']
else:
fname_mask = ''
padding = arguments['-z']
if "-param" in arguments:
paramreg_user = arguments['-param']
# update registration parameters
for paramStep in paramreg_user:
paramreg.addStep(paramStep)
identity = int(arguments['-identity'])
interp = arguments['-x']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments['-v'])
# print arguments
print '\nInput parameters:'
print ' Source .............. '+fname_src
print ' Destination ......... '+fname_dest
print ' Init transfo ........ '+fname_initwarp
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 user selected type=seg, but did not input segmentation data
if 'paramreg_user' in locals():
if True in ['type=seg' in paramreg_user[i] for i in range(len(paramreg_user))]:
if fname_src_seg == '' or fname_dest_seg == '':
sct.printv('\nERROR: if you select type=seg you must specify -iseg and -dseg flags.\n', 1, 'error')
# 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)
# check if source and destination images have the same name (related to issue #373)
# If so, change names to avoid conflict of result files and warns the user
suffix_src, suffix_dest = '_reg', '_reg'
if file_src == file_dest:
suffix_src, suffix_dest = '_src_reg', '_dest_reg'
# define output folder and file name
if fname_output == '':
path_out = '' if not path_out else path_out # output in user's current directory
file_out = file_src + suffix_src
file_out_inv = file_dest + suffix_dest
ext_out = ext_src
else:
path, file_out, ext_out = sct.extract_fname(fname_output)
path_out = path if not path_out else path_out
file_out_inv = file_out + '_inv'
# create QC folder
sct.create_folder(param.path_qc)
# create temporary folder
path_tmp = sct.tmp_create()
# copy files to temporary folder
from sct_convert import convert
sct.printv('\nCopying input data to tmp folder and convert to nii...', verbose)
convert(fname_src, path_tmp+'src.nii')
convert(fname_dest, path_tmp+'dest.nii')
if fname_src_seg:
convert(fname_src_seg, path_tmp+'src_seg.nii')
convert(fname_dest_seg, path_tmp+'dest_seg.nii')
if fname_src_label:
convert(fname_src_label, path_tmp+'src_label.nii')
convert(fname_dest_label, path_tmp+'dest_label.nii')
if fname_mask != '':
convert(fname_mask, path_tmp+'mask.nii.gz')
# go to tmp folder
os.chdir(path_tmp)
# reorient destination to RPI
sct.run('sct_image -i dest.nii -setorient RPI -o dest_RPI.nii')
if fname_dest_seg:
sct.run('sct_image -i dest_seg.nii -setorient RPI -o dest_seg_RPI.nii')
if fname_dest_label:
sct.run('sct_image -i dest_label.nii -setorient RPI -o dest_label_RPI.nii')
if identity:
# overwrite paramreg and only do one identity transformation
step0 = Paramreg(step='0', type='im', algo='syn', metric='MI', iter='0', shrink='1', smooth='0', gradStep='0.5')
paramreg = ParamregMultiStep([step0])
# Put source into destination space using header (no estimation -- purely based on header)
# 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
# initialize list of warping fields
warp_forward = []
warp_inverse = []
# initial warping is specified, update list of warping fields and skip step=0
if fname_initwarp:
sct.printv('\nSkip step=0 and replace with initial transformations: ', param.verbose)
sct.printv(' '+fname_initwarp, param.verbose)
# sct.run('cp '+fname_initwarp+' warp_forward_0.nii.gz', verbose)
warp_forward = [fname_initwarp]
start_step = 1
if fname_initwarpinv:
warp_inverse = [fname_initwarpinv]
else:
sct.printv('\nWARNING: No initial inverse warping field was specified, therefore the inverse warping field will NOT be generated.', param.verbose, 'warning')
generate_warpinv = 0
else:
start_step = 0
# loop across registration steps
for i_step in range(start_step, len(paramreg.steps)):
sct.printv('\n--\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_RPI.nii'
interp_step = 'spline'
elif paramreg.steps[str(i_step)].type == 'seg':
src = 'src_seg.nii'
dest = 'dest_seg_RPI.nii'
interp_step = 'nn'
elif paramreg.steps[str(i_step)].type == 'label':
src = 'src_label.nii'
dest = 'dest_label_RPI.nii'
interp_step = 'nn'
else:
# src = dest = interp_step = None
sct.printv('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.printv('\nApply transformation from previous step', param.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.insert(0, 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)
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)
# generate: src_reg
fname_src2dest = sct.generate_output_file(path_tmp+'src_reg.nii', path_out+file_out+ext_out, verbose)
# generate: forward warping field
if fname_output_warp == '':
fname_output_warp = path_out+'warp_'+file_src+'2'+file_dest+'.nii.gz'
sct.generate_output_file(path_tmp+'warp_src2dest.nii.gz', fname_output_warp, verbose)
if generate_warpinv:
# generate: dest_reg
fname_dest2src = sct.generate_output_file(path_tmp+'dest_reg.nii', path_out+file_out_inv+ext_dest, verbose)
# generate: inverse warping field
sct.generate_output_file(path_tmp+'warp_dest2src.nii.gz', path_out+'warp_'+file_dest+'2'+file_src+'.nii.gz', verbose)
# 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')
if generate_warpinv:
sct.printv('fslview '+fname_src+' '+fname_dest2src+' &\n', verbose, 'info')
def apply(self):
# Initialization
fname_src = self.input_filename # source image (moving)
fname_warp_list = self.warp_input # list of warping fields
fname_out = self.output_filename # output
fname_dest = self.fname_dest # destination image (fix)
verbose = self.verbose
remove_temp_files = self.remove_temp_files
crop_reference = self.crop # if = 1, put 0 everywhere around warping field, if = 2, real crop
interp = sct.get_interpolation('isct_antsApplyTransforms', self.interp)
# Parse list of warping fields
sct.printv('\nParse list of warping fields...', verbose)
use_inverse = []
fname_warp_list_invert = []
# fname_warp_list = fname_warp_list.replace(' ', '') # remove spaces
# fname_warp_list = fname_warp_list.split(",") # parse with comma
for idx_warp, path_warp in enumerate(fname_warp_list):
# Check if inverse matrix is specified with '-' at the beginning of file name
if path_warp.startswith("-"):
use_inverse.append('-i')
fname_warp_list[idx_warp] = path_warp[1:] # remove '-'
fname_warp_list_invert += [[use_inverse[idx_warp], fname_warp_list[idx_warp]]]
else:
use_inverse.append('')
fname_warp_list_invert += [[path_warp]]
path_warp = fname_warp_list[idx_warp]
if path_warp.endswith((".nii", ".nii.gz")) \
and msct_image.Image(fname_warp_list[idx_warp]).header.get_intent()[0] != 'vector':
raise ValueError("Displacement field in {} is invalid: should be encoded" \
" in a 5D file with vector intent code" \
" (see https://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h" \
.format(path_warp))
# need to check if last warping field is an affine transfo
isLastAffine = False
path_fname, file_fname, ext_fname = sct.extract_fname(fname_warp_list_invert[-1][-1])
if ext_fname in ['.txt', '.mat']:
isLastAffine = True
# check if destination file is 3d
if not sct.check_if_3d(fname_dest):
sct.printv('ERROR: Destination data must be 3d')
# N.B. Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order
fname_warp_list_invert.reverse()
fname_warp_list_invert = functools.reduce(lambda x,y: x+y, fname_warp_list_invert)
# 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)
# Get output folder and file name
if fname_out == '':
path_out = '' # output in user's current directory
file_out = file_src + '_reg'
ext_out = ext_src
fname_out = os.path.join(path_out, file_out + ext_out)
# Get dimensions of data
sct.printv('\nGet dimensions of data...', verbose)
img_src = msct_image.Image(fname_src)
nx, ny, nz, nt, px, py, pz, pt = img_src.dim
# nx, ny, nz, nt, px, py, pz, pt = sct.get_dimension(fname_src)
sct.printv(' ' + str(nx) + ' x ' + str(ny) + ' x ' + str(nz) + ' x ' + str(nt), verbose)
# if 3d
if nt == 1:
# Apply transformation
sct.printv('\nApply transformation...', verbose)
if nz in [0, 1]:
dim = '2'
else:
dim = '3'
sct.run(['isct_antsApplyTransforms',
'-d', dim,
'-i', fname_src,
'-o', fname_out,
'-t',
] + fname_warp_list_invert + [
'-r', fname_dest,
] + interp, verbose=verbose, is_sct_binary=True)
# if 4d, loop across the T dimension
else:
path_tmp = sct.tmp_create(basename="apply_transfo", verbose=verbose)
# convert to nifti into temp folder
sct.printv('\nCopying input data to tmp folder and convert to nii...', verbose)
img_src.save(os.path.join(path_tmp, "data.nii"))
sct.copy(fname_dest, os.path.join(path_tmp, file_dest + ext_dest))
fname_warp_list_tmp = []
for fname_warp in fname_warp_list:
path_warp, file_warp, ext_warp = sct.extract_fname(fname_warp)
sct.copy(fname_warp, os.path.join(path_tmp, file_warp + ext_warp))
fname_warp_list_tmp.append(file_warp + ext_warp)
fname_warp_list_invert_tmp = fname_warp_list_tmp[::-1]
curdir = os.getcwd()
os.chdir(path_tmp)
# split along T dimension
sct.printv('\nSplit along T dimension...', verbose)
im_dat = msct_image.Image('data.nii')
im_header = im_dat.hdr
data_split_list = sct_image.split_data(im_dat, 3)
for im in data_split_list:
im.save()
# apply transfo
sct.printv('\nApply transformation to each 3D volume...', verbose)
for it in range(nt):
file_data_split = 'data_T' + str(it).zfill(4) + '.nii'
file_data_split_reg = 'data_reg_T' + str(it).zfill(4) + '.nii'
status, output = sct.run(['isct_antsApplyTransforms',
'-d', '3',
'-i', file_data_split,
'-o', file_data_split_reg,
'-t',
] + fname_warp_list_invert_tmp + [
'-r', file_dest + ext_dest,
] + interp, verbose, is_sct_binary=True)
# Merge files back
sct.printv('\nMerge file back...', verbose)
import glob
path_out, name_out, ext_out = sct.extract_fname(fname_out)
# im_list = [Image(file_name) for file_name in glob.glob('data_reg_T*.nii')]
# concat_data use to take a list of image in input, now takes a list of file names to open the files one by one (see issue #715)
fname_list = glob.glob('data_reg_T*.nii')
fname_list.sort()
im_out = sct_image.concat_data(fname_list, 3, im_header['pixdim'])
im_out.save(name_out + ext_out)
os.chdir(curdir)
sct.generate_output_file(os.path.join(path_tmp, name_out + ext_out), fname_out)
# Delete temporary folder if specified
if int(remove_temp_files):
sct.printv('\nRemove temporary files...', verbose)
sct.rmtree(path_tmp, verbose=verbose)
# 2. crop the resulting image using dimensions from the warping field
warping_field = fname_warp_list_invert[-1]
# if last warping field is an affine transfo, we need to compute the space of the concatenate warping field:
if isLastAffine:
sct.printv('WARNING: the resulting image could have wrong apparent results. You should use an affine transformation as last transformation...', verbose, 'warning')
elif crop_reference == 1:
ImageCropper(input_file=fname_out, output_file=fname_out, ref=warping_field, background=0).crop()
# sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field+' -b 0')
elif crop_reference == 2:
ImageCropper(input_file=fname_out, output_file=fname_out, ref=warping_field).crop()
# sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field)
sct.display_viewer_syntax([fname_dest, fname_out], verbose=verbose)
def apply(self):
# Initialization
fname_src = self.input_filename # source image (moving)
fname_warp_list = self.warp_input # list of warping fields
fname_out = self.output_filename # output
fname_dest = self.fname_dest # destination image (fix)
verbose = self.verbose
remove_temp_files = self.remove_temp_files
crop_reference = self.crop # if = 1, put 0 everywhere around warping field, if = 2, real crop
interp = sct.get_interpolation('isct_antsApplyTransforms', self.interp)
# Parse list of warping fields
sct.printv('\nParse list of warping fields...', verbose)
use_inverse = []
fname_warp_list_invert = []
# fname_warp_list = fname_warp_list.replace(' ', '') # remove spaces
# fname_warp_list = fname_warp_list.split(",") # parse with comma
for i in range(len(fname_warp_list)):
# Check if inverse matrix is specified with '-' at the beginning of file name
if fname_warp_list[i].find('-') == 0:
use_inverse.append('-i ')
fname_warp_list[i] = fname_warp_list[i][1:] # remove '-'
else:
use_inverse.append('')
sct.printv(
' Transfo #' + str(i) + ': ' + use_inverse[i] +
fname_warp_list[i], verbose)
fname_warp_list_invert.append(use_inverse[i] + fname_warp_list[i])
# need to check if last warping field is an affine transfo
isLastAffine = False
path_fname, file_fname, ext_fname = sct.extract_fname(
fname_warp_list_invert[-1])
if ext_fname in ['.txt', '.mat']:
isLastAffine = True
# check if destination file is 3d
if not sct.check_if_3d(fname_dest):
sct.printv('ERROR: Destination data must be 3d')
# N.B. Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order
fname_warp_list_invert.reverse()
# 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)
# Get output folder and file name
if fname_out == '':
path_out = '' # output in user's current directory
file_out = file_src + '_reg'
ext_out = ext_src
fname_out = path_out + file_out + ext_out
# Get dimensions of data
sct.printv('\nGet dimensions of data...', verbose)
from msct_image import Image
nx, ny, nz, nt, px, py, pz, pt = Image(fname_src).dim
# nx, ny, nz, nt, px, py, pz, pt = sct.get_dimension(fname_src)
sct.printv(
' ' + str(nx) + ' x ' + str(ny) + ' x ' + str(nz) + ' x ' +
str(nt), verbose)
# if 3d
if nt == 1:
# Apply transformation
sct.printv('\nApply transformation...', verbose)
if nz in [0, 1]:
dim = '2'
else:
dim = '3'
sct.run(
'isct_antsApplyTransforms -d ' + dim + ' -i ' + fname_src +
' -o ' + fname_out + ' -t ' +
' '.join(fname_warp_list_invert) + ' -r ' + fname_dest +
interp, verbose)
# if 4d, loop across the T dimension
else:
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = sct.slash_at_the_end(
'tmp.' + time.strftime("%y%m%d%H%M%S"), 1)
# sct.run('mkdir '+path_tmp, verbose)
sct.run('mkdir ' + path_tmp, verbose)
# convert to nifti into temp folder
sct.printv(
'\nCopying input data to tmp folder and convert to nii...',
verbose)
from sct_convert import convert
convert(fname_src, path_tmp + 'data.nii', squeeze_data=False)
sct.run('cp ' + fname_dest + ' ' + path_tmp + file_dest + ext_dest)
fname_warp_list_tmp = []
for fname_warp in fname_warp_list:
path_warp, file_warp, ext_warp = sct.extract_fname(fname_warp)
sct.run('cp ' + fname_warp + ' ' + path_tmp + file_warp +
ext_warp)
fname_warp_list_tmp.append(file_warp + ext_warp)
fname_warp_list_invert_tmp = fname_warp_list_tmp[::-1]
os.chdir(path_tmp)
# split along T dimension
sct.printv('\nSplit along T dimension...', verbose)
from sct_image import split_data
im_dat = Image('data.nii')
im_header = im_dat.hdr
data_split_list = split_data(im_dat, 3)
for im in data_split_list:
im.save()
# apply transfo
sct.printv('\nApply transformation to each 3D volume...', verbose)
for it in range(nt):
file_data_split = 'data_T' + str(it).zfill(4) + '.nii'
file_data_split_reg = 'data_reg_T' + str(it).zfill(4) + '.nii'
status, output = sct.run(
'isct_antsApplyTransforms -d 3 -i ' + file_data_split +
' -o ' + file_data_split_reg + ' -t ' +
' '.join(fname_warp_list_invert_tmp) + ' -r ' + file_dest +
ext_dest + interp, verbose)
# Merge files back
sct.printv('\nMerge file back...', verbose)
from sct_image import concat_data
import glob
path_out, name_out, ext_out = sct.extract_fname(fname_out)
# im_list = [Image(file_name) for file_name in glob.glob('data_reg_T*.nii')]
# concat_data use to take a list of image in input, now takes a list of file names to open the files one by one (see issue #715)
fname_list = glob.glob('data_reg_T*.nii')
im_out = concat_data(fname_list, 3, im_header['pixdim'])
im_out.setFileName(name_out + ext_out)
im_out.save(squeeze_data=False)
os.chdir('..')
sct.generate_output_file(path_tmp + name_out + ext_out, fname_out)
# Delete temporary folder if specified
if int(remove_temp_files):
sct.printv('\nRemove temporary files...', verbose)
sct.run('rm -rf ' + path_tmp, verbose, error_exit='warning')
# 2. crop the resulting image using dimensions from the warping field
warping_field = fname_warp_list_invert[-1]
# if last warping field is an affine transfo, we need to compute the space of the concatenate warping field:
if isLastAffine:
sct.printv(
'WARNING: the resulting image could have wrong apparent results. You should use an affine transformation as last transformation...',
verbose, 'warning')
elif crop_reference == 1:
ImageCropper(input_file=fname_out,
output_file=fname_out,
ref=warping_field,
background=0).crop()
# sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field+' -b 0')
elif crop_reference == 2:
ImageCropper(input_file=fname_out,
output_file=fname_out,
ref=warping_field).crop()
# sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field)
# display elapsed time
sct.printv('\nDone! To view results, type:', verbose)
sct.printv('fslview ' + fname_dest + ' ' + fname_out + ' &\n', verbose,
'info')
def main(args=None):
if args is None:
args = sys.argv[1:]
# initialize parameters
param = Param()
# Initialization
fname_output = ''
path_out = ''
fname_src_seg = ''
fname_dest_seg = ''
fname_src_label = ''
fname_dest_label = ''
generate_warpinv = 1
start_time = time.time()
# 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',
slicewise='0', dof='Tx_Ty_Tz_Rx_Ry_Rz') # only used to put src into dest space
step1 = Paramreg(step='1', type='im')
paramreg = ParamregMultiStep([step0, step1])
parser = get_parser(paramreg=paramreg)
arguments = parser.parse(args)
# 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 '-ilabel' in arguments:
fname_src_label = arguments['-ilabel']
if '-dlabel' in arguments:
fname_dest_label = arguments['-dlabel']
if '-o' in arguments:
fname_output = arguments['-o']
if '-ofolder' in arguments:
path_out = arguments['-ofolder']
if '-owarp' in arguments:
fname_output_warp = arguments['-owarp']
else:
fname_output_warp = ''
if '-initwarp' in arguments:
fname_initwarp = os.path.abspath(arguments['-initwarp'])
else:
fname_initwarp = ''
if '-initwarpinv' in arguments:
fname_initwarpinv = os.path.abspath(arguments['-initwarpinv'])
else:
fname_initwarpinv = ''
if '-m' in arguments:
fname_mask = arguments['-m']
else:
fname_mask = ''
padding = arguments['-z']
if "-param" in arguments:
paramreg_user = arguments['-param']
# update registration parameters
for paramStep in paramreg_user:
paramreg.addStep(paramStep)
path_qc = arguments.get("-qc", None)
qc_dataset = arguments.get("-qc-dataset", None)
qc_subject = arguments.get("-qc-subject", None)
identity = int(arguments['-identity'])
interp = arguments['-x']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments.get('-v'))
sct.init_sct(log_level=verbose, update=True) # Update log level
# sct.printv(arguments)
sct.printv('\nInput parameters:')
sct.printv(' Source .............. ' + fname_src)
sct.printv(' Destination ......... ' + fname_dest)
sct.printv(' Init transfo ........ ' + fname_initwarp)
sct.printv(' Mask ................ ' + fname_mask)
sct.printv(' Output name ......... ' + fname_output)
# sct.printv(' Algorithm ........... '+paramreg.algo)
# sct.printv(' Number of iterations '+paramreg.iter)
# sct.printv(' Metric .............. '+paramreg.metric)
sct.printv(' Remove temp files ... ' + str(remove_temp_files))
sct.printv(' 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 user selected type=seg, but did not input segmentation data
if 'paramreg_user' in locals():
if True in ['type=seg' in paramreg_user[i] for i in range(len(paramreg_user))]:
if fname_src_seg == '' or fname_dest_seg == '':
sct.printv('\nERROR: if you select type=seg you must specify -iseg and -dseg flags.\n', 1, 'error')
# 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)
# check if source and destination images have the same name (related to issue #373)
# If so, change names to avoid conflict of result files and warns the user
suffix_src, suffix_dest = '_reg', '_reg'
if file_src == file_dest:
suffix_src, suffix_dest = '_src_reg', '_dest_reg'
# define output folder and file name
if fname_output == '':
path_out = '' if not path_out else path_out # output in user's current directory
file_out = file_src + suffix_src
file_out_inv = file_dest + suffix_dest
ext_out = ext_src
else:
path, file_out, ext_out = sct.extract_fname(fname_output)
path_out = path if not path_out else path_out
file_out_inv = file_out + '_inv'
# create temporary folder
path_tmp = sct.tmp_create()
sct.printv('\nCopying input data to tmp folder and convert to nii...', verbose)
Image(fname_src).save(os.path.join(path_tmp, "src.nii"))
Image(fname_dest).save(os.path.join(path_tmp, "dest.nii"))
if fname_src_seg:
Image(fname_src_seg).save(os.path.join(path_tmp, "src_seg.nii"))
if fname_dest_seg:
Image(fname_dest_seg).save(os.path.join(path_tmp, "dest_seg.nii"))
if fname_src_label:
Image(fname_src_label).save(os.path.join(path_tmp, "src_label.nii"))
Image(fname_dest_label).save(os.path.join(path_tmp, "dest_label.nii"))
if fname_mask != '':
Image(fname_mask).save(os.path.join(path_tmp, "mask.nii.gz"))
# go to tmp folder
curdir = os.getcwd()
os.chdir(path_tmp)
# reorient destination to RPI
Image('dest.nii').change_orientation("RPI").save('dest_RPI.nii')
if fname_dest_seg:
Image('dest_seg.nii').change_orientation("RPI").save('dest_seg_RPI.nii')
if fname_dest_label:
Image('dest_label.nii').change_orientation("RPI").save('dest_label_RPI.nii')
if identity:
# overwrite paramreg and only do one identity transformation
step0 = Paramreg(step='0', type='im', algo='syn', metric='MI', iter='0', shrink='1', smooth='0', gradStep='0.5')
paramreg = ParamregMultiStep([step0])
# Put source into destination space using header (no estimation -- purely based on header)
# 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
# initialize list of warping fields
warp_forward = []
warp_inverse = []
# initial warping is specified, update list of warping fields and skip step=0
if fname_initwarp:
sct.printv('\nSkip step=0 and replace with initial transformations: ', param.verbose)
sct.printv(' ' + fname_initwarp, param.verbose)
# sct.copy(fname_initwarp, 'warp_forward_0.nii.gz')
warp_forward = [fname_initwarp]
start_step = 1
if fname_initwarpinv:
warp_inverse = [fname_initwarpinv]
else:
sct.printv('\nWARNING: No initial inverse warping field was specified, therefore the inverse warping field '
'will NOT be generated.', param.verbose, 'warning')
generate_warpinv = 0
else:
start_step = 0
# loop across registration steps
for i_step in range(start_step, len(paramreg.steps)):
sct.printv('\n--\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_RPI.nii'
interp_step = 'spline'
elif paramreg.steps[str(i_step)].type == 'seg':
src = 'src_seg.nii'
dest = 'dest_seg_RPI.nii'
interp_step = 'nn'
elif paramreg.steps[str(i_step)].type == 'label':
src = 'src_label.nii'
dest = 'dest_label_RPI.nii'
interp_step = 'nn'
else:
# src = dest = interp_step = None
sct.printv('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.printv('\nApply transformation from previous step', param.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.insert(0, 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)
sct.run(['sct_concat_transfo', '-w', ','.join(warp_inverse), '-d', 'src.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
os.chdir(curdir)
# Generate output files
sct.printv('\nGenerate output files...', verbose)
# generate: src_reg
fname_src2dest = sct.generate_output_file(os.path.join(path_tmp, "src_reg.nii"),
os.path.join(path_out, file_out + ext_out), verbose)
# generate: forward warping field
if fname_output_warp == '':
fname_output_warp = os.path.join(path_out, 'warp_' + file_src + '2' + file_dest + '.nii.gz')
sct.generate_output_file(os.path.join(path_tmp, "warp_src2dest.nii.gz"), fname_output_warp, verbose)
if generate_warpinv:
# generate: dest_reg
fname_dest2src = sct.generate_output_file(os.path.join(path_tmp, "dest_reg.nii"),
os.path.join(path_out, file_out_inv + ext_dest), verbose)
# generate: inverse warping field
sct.generate_output_file(os.path.join(path_tmp, "warp_dest2src.nii.gz"),
os.path.join(path_out, 'warp_' + file_dest + '2' + file_src + '.nii.gz'), verbose)
# Delete temporary files
if remove_temp_files:
sct.printv('\nRemove temporary files...', verbose)
sct.rmtree(path_tmp, verbose=verbose)
# display elapsed time
elapsed_time = time.time() - start_time
sct.printv('\nFinished! Elapsed time: ' + str(int(np.round(elapsed_time))) + 's', verbose)
if path_qc is not None:
if fname_dest_seg:
generate_qc(fname_src2dest, fname_in2=fname_dest, fname_seg=fname_dest_seg, args=args,
path_qc=os.path.abspath(path_qc), dataset=qc_dataset, subject=qc_subject,
process='sct_register_multimodal')
else:
sct.printv('WARNING: Cannot generate QC because it requires destination segmentation.', 1, 'warning')
if generate_warpinv:
sct.display_viewer_syntax([fname_src, fname_dest2src], verbose=verbose)
sct.display_viewer_syntax([fname_dest, fname_src2dest], verbose=verbose)
def main(args=None):
if args is None:
args = sys.argv[1:]
# initialize parameters
param = Param()
# Initialization
fname_output = ''
path_out = ''
fname_src_seg = ''
fname_dest_seg = ''
fname_src_label = ''
fname_dest_label = ''
generate_warpinv = 1
start_time = time.time()
# 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',
slicewise='0',
dof='Tx_Ty_Tz_Rx_Ry_Rz') # only used to put src into dest space
step1 = Paramreg(step='1', type='im')
paramregmulti = ParamregMultiStep([step0, step1])
parser = get_parser(paramregmulti=paramregmulti)
arguments = parser.parse(args)
# 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 '-ilabel' in arguments:
fname_src_label = arguments['-ilabel']
if '-dlabel' in arguments:
fname_dest_label = arguments['-dlabel']
if '-o' in arguments:
fname_output = arguments['-o']
if '-ofolder' in arguments:
path_out = arguments['-ofolder']
if '-owarp' in arguments:
fname_output_warp = arguments['-owarp']
else:
fname_output_warp = ''
if '-initwarp' in arguments:
fname_initwarp = os.path.abspath(arguments['-initwarp'])
else:
fname_initwarp = ''
if '-initwarpinv' in arguments:
fname_initwarpinv = os.path.abspath(arguments['-initwarpinv'])
else:
fname_initwarpinv = ''
if '-m' in arguments:
fname_mask = arguments['-m']
else:
fname_mask = ''
padding = arguments['-z']
if "-param" in arguments:
paramregmulti_user = arguments['-param']
# update registration parameters
for paramStep in paramregmulti_user:
paramregmulti.addStep(paramStep)
path_qc = arguments.get("-qc", None)
qc_dataset = arguments.get("-qc-dataset", None)
qc_subject = arguments.get("-qc-subject", None)
identity = int(arguments['-identity'])
interp = arguments['-x']
remove_temp_files = int(arguments['-r'])
verbose = int(arguments.get('-v'))
sct.init_sct(log_level=verbose, update=True) # Update log level
# sct.printv(arguments)
sct.printv('\nInput parameters:')
sct.printv(' Source .............. ' + fname_src)
sct.printv(' Destination ......... ' + fname_dest)
sct.printv(' Init transfo ........ ' + fname_initwarp)
sct.printv(' Mask ................ ' + fname_mask)
sct.printv(' Output name ......... ' + fname_output)
# sct.printv(' Algorithm ........... '+paramregmulti.algo)
# sct.printv(' Number of iterations '+paramregmulti.iter)
# sct.printv(' Metric .............. '+paramregmulti.metric)
sct.printv(' Remove temp files ... ' + str(remove_temp_files))
sct.printv(' 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 user selected type=seg, but did not input segmentation data
if 'paramregmulti_user' in locals():
if True in [
'type=seg' in paramregmulti_user[i]
for i in range(len(paramregmulti_user))
]:
if fname_src_seg == '' or fname_dest_seg == '':
sct.printv(
'\nERROR: if you select type=seg you must specify -iseg and -dseg flags.\n',
1, 'error')
# Put source into destination space using header (no estimation -- purely based on header)
# 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
fname_src2dest, fname_dest2src, _, _ = \
register_wrapper(fname_src, fname_dest, param, paramregmulti, fname_src_seg=fname_src_seg,
fname_dest_seg=fname_dest_seg, fname_src_label=fname_src_label,
fname_dest_label=fname_dest_label, fname_mask=fname_mask, fname_initwarp=fname_initwarp,
fname_initwarpinv=fname_initwarpinv, identity=identity, interp=interp,
fname_output=fname_output,
fname_output_warp=fname_output_warp,
path_out=path_out)
# display elapsed time
elapsed_time = time.time() - start_time
sct.printv(
'\nFinished! Elapsed time: ' + str(int(np.round(elapsed_time))) + 's',
verbose)
if path_qc is not None:
if fname_dest_seg:
generate_qc(fname_src2dest,
fname_in2=fname_dest,
fname_seg=fname_dest_seg,
args=args,
path_qc=os.path.abspath(path_qc),
dataset=qc_dataset,
subject=qc_subject,
process='sct_register_multimodal')
else:
sct.printv(
'WARNING: Cannot generate QC because it requires destination segmentation.',
1, 'warning')
if generate_warpinv:
sct.display_viewer_syntax([fname_src, fname_dest2src], verbose=verbose)
sct.display_viewer_syntax([fname_dest, fname_src2dest], verbose=verbose)
def apply(self):
# Initialization
fname_src = self.input_filename # source image (moving)
fname_warp_list = self.warp_input # list of warping fields
fname_out = self.output_filename # output
fname_dest = self.fname_dest # destination image (fix)
verbose = self.verbose
remove_temp_files = self.remove_temp_files
crop_reference = self.crop # if = 1, put 0 everywhere around warping field, if = 2, real crop
interp = sct.get_interpolation('isct_antsApplyTransforms', self.interp)
# Parse list of warping fields
sct.printv('\nParse list of warping fields...', verbose)
use_inverse = []
fname_warp_list_invert = []
# fname_warp_list = fname_warp_list.replace(' ', '') # remove spaces
# fname_warp_list = fname_warp_list.split(",") # parse with comma
for i in range(len(fname_warp_list)):
# Check if inverse matrix is specified with '-' at the beginning of file name
if fname_warp_list[i].find('-') == 0:
use_inverse.append('-i ')
fname_warp_list[i] = fname_warp_list[i][1:] # remove '-'
else:
use_inverse.append('')
sct.printv(' Transfo #'+str(i)+': '+use_inverse[i]+fname_warp_list[i], verbose)
fname_warp_list_invert.append(use_inverse[i]+fname_warp_list[i])
# need to check if last warping field is an affine transfo
isLastAffine = False
path_fname, file_fname, ext_fname = sct.extract_fname(fname_warp_list_invert[-1])
if ext_fname in ['.txt', '.mat']:
isLastAffine = True
# Check file existence
sct.printv('\nCheck file existence...', verbose)
sct.check_file_exist(fname_src, self.verbose)
sct.check_file_exist(fname_dest, self.verbose)
for i in range(len(fname_warp_list)):
# check if file exist
sct.check_file_exist(fname_warp_list[i], self.verbose)
# check if destination file is 3d
if not sct.check_if_3d(fname_dest):
sct.printv('ERROR: Destination data must be 3d')
# N.B. Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order
fname_warp_list_invert.reverse()
# 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)
# Get output folder and file name
if fname_out == '':
path_out = '' # output in user's current directory
file_out = file_src+'_reg'
ext_out = ext_src
fname_out = path_out+file_out+ext_out
# Get dimensions of data
sct.printv('\nGet dimensions of data...', verbose)
from msct_image import Image
nx, ny, nz, nt, px, py, pz, pt = Image(fname_src).dim
# nx, ny, nz, nt, px, py, pz, pt = sct.get_dimension(fname_src)
sct.printv(' ' + str(nx) + ' x ' + str(ny) + ' x ' + str(nz)+ ' x ' + str(nt), verbose)
# if 3d
if nt == 1:
# Apply transformation
sct.printv('\nApply transformation...', verbose)
sct.run('isct_antsApplyTransforms -d 3 -i '+fname_src+' -o '+fname_out+' -t '+' '.join(fname_warp_list_invert)+' -r '+fname_dest+interp, verbose)
# if 4d, loop across the T dimension
else:
# create temporary folder
sct.printv('\nCreate temporary folder...', verbose)
path_tmp = sct.slash_at_the_end('tmp.'+time.strftime("%y%m%d%H%M%S"), 1)
# sct.run('mkdir '+path_tmp, verbose)
sct.run('mkdir '+path_tmp, verbose)
# convert to nifti into temp folder
sct.printv('\nCopying input data to tmp folder and convert to nii...', verbose)
from sct_convert import convert
convert(fname_src, path_tmp+'data.nii')
# split along T dimension
sct.printv('\nSplit along T dimension...', verbose)
from sct_split_data import split_data
if not split_data(path_tmp+'data.nii', 3, '_T'):
sct.printv('ERROR in split_data.', 1, 'error')
# apply transfo
sct.printv('\nApply transformation to each 3D volume...', verbose)
for it in range(nt):
file_data_split = path_tmp+'data_T'+str(it).zfill(4)+'.nii'
file_data_split_reg = path_tmp+'data_reg_T'+str(it).zfill(4)+'.nii'
sct.run('isct_antsApplyTransforms -d 3 -i '+file_data_split+' -o '+file_data_split_reg+' -t '+' '.join(fname_warp_list_invert)+' -r '+fname_dest+interp, verbose)
# Merge files back
sct.printv('\nMerge file back...', verbose)
from sct_concat_data import concat_data
import glob
concat_data(glob.glob(path_tmp+'data_reg_T*.nii'), fname_out, dim=3)
# Delete temporary folder if specified
if int(remove_temp_files):
sct.printv('\nRemove temporary files...', verbose)
sct.run('rm -rf '+path_tmp, verbose)
# 2. crop the resulting image using dimensions from the warping field
warping_field = fname_warp_list_invert[-1]
# if last warping field is an affine transfo, we need to compute the space of the concatenate warping field:
if isLastAffine:
sct.printv('WARNING: the resulting image could have wrong apparent results. You should use an affine transformation as last transformation...',verbose,'warning')
elif crop_reference == 1:
ImageCropper(input_file=fname_out, output_file=fname_out, ref=warping_field, background=0).crop()
# sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field+' -b 0')
elif crop_reference == 2:
ImageCropper(input_file=fname_out, output_file=fname_out, ref=warping_field).crop()
# sct.run('sct_crop_image -i '+fname_out+' -o '+fname_out+' -ref '+warping_field)
# display elapsed time
sct.printv('\nDone! To view results, type:', verbose)
sct.printv('fslview '+fname_dest+' '+fname_out+' &\n', verbose, 'info')
