def run_main():
sct.init_sct()
parser = get_parser()
args = sys.argv[1:]
arguments = parser.parse(args)
# Input filename
fname_input_data = arguments["-i"]
fname_data = os.path.abspath(fname_input_data)
# Method used
method = 'optic'
if "-method" in arguments:
method = arguments["-method"]
# Contrast type
contrast_type = ''
if "-c" in arguments:
contrast_type = arguments["-c"]
if method == 'optic' and not contrast_type:
# Contrast must be
error = 'ERROR: -c is a mandatory argument when using Optic method.'
sct.printv(error, type='error')
return
# Ga between slices
interslice_gap = 10.0
if "-gap" in arguments:
interslice_gap = float(arguments["-gap"])
# Output folder
if "-ofolder" in arguments:
folder_output = arguments["-ofolder"]
else:
folder_output = '.'
# Remove temporary files
remove_temp_files = True
if "-r" in arguments:
remove_temp_files = bool(int(arguments["-r"]))
# Outputs a ROI file
output_roi = False
if "-roi" in arguments:
output_roi = bool(int(arguments["-roi"]))
# Verbosity
verbose = 0
if "-v" in arguments:
verbose = int(arguments["-v"])
if method == 'viewer':
fname_labels_viewer = _call_viewer_centerline(
fname_in=fname_data, interslice_gap=interslice_gap)
centerline_filename = extract_centerline(
fname_labels_viewer,
remove_temp_files=remove_temp_files,
verbose=verbose,
algo_fitting='nurbs',
nurbs_pts_number=8000)
else:
# condition on verbose when using OptiC
if verbose == 1:
verbose = 2
# OptiC models
path_script = os.path.dirname(__file__)
path_sct = os.path.dirname(path_script)
optic_models_path = os.path.join(path_sct, 'data', 'optic_models',
'{}_model'.format(contrast_type))
# Execute OptiC binary
_, centerline_filename = optic.detect_centerline(
image_fname=fname_data,
contrast_type=contrast_type,
optic_models_path=optic_models_path,
folder_output=folder_output,
remove_temp_files=remove_temp_files,
output_roi=output_roi,
verbose=verbose)
sct.display_viewer_syntax([fname_input_data, centerline_filename],
colormaps=['gray', 'red'],
opacities=['', '1'])
def get_centerline_from_labels(
fname_in, list_fname_labels, param, output_file_name=None, remove_temp_files=1, verbose=0
):
path, file, ext = sct.extract_fname(fname_in)
# create temporary folder
path_tmp = sct.slash_at_the_end("tmp." + strftime("%y%m%d%H%M%S"), 1)
sct.run("mkdir " + path_tmp)
# Copying input data to tmp folder
sct.printv("\nCopying input data to tmp folder...", verbose)
sct.run("sct_convert -i " + fname_in + " -o " + path_tmp + "data.nii")
file_labels = []
for i in range(len(list_fname_labels)):
file_labels.append("labels_" + str(i) + ".nii.gz")
sct.run("sct_convert -i " + list_fname_labels[i] + " -o " + path_tmp + file_labels[i])
# go to tmp folder
os.chdir(path_tmp)
## Concatenation of the files
# Concatenation : sum of matrices
file_0 = Image("data.nii")
data_concatenation = file_0.data
hdr_0 = file_0.hdr
orientation_file_0 = get_orientation_3d(file_0)
if len(list_fname_labels) > 0:
for i in range(0, len(list_fname_labels)):
orientation_file_temp = get_orientation_3d(file_labels[i], filename=True)
if orientation_file_0 != orientation_file_temp:
print "ERROR: The files ", fname_in, " and ", file_labels[
i
], " are not in the same orientation. Use sct_image -setorient to change the orientation of a file."
sys.exit(2)
file_temp = load(file_labels[i])
data_temp = file_temp.get_data()
data_concatenation = data_concatenation + data_temp
# Save concatenation as a file
print "\nWrite NIFTI volumes..."
img = Nifti1Image(data_concatenation, None, hdr_0)
save(img, "concatenation_file.nii.gz")
# Applying nurbs to the concatenation and save file as binary file
fname_output = extract_centerline(
"concatenation_file.nii.gz",
remove_temp_files=remove_temp_files,
verbose=verbose,
algo_fitting=param.algo_fitting,
type_window=param.type_window,
window_length=param.window_length,
)
# Rename files after processing
if output_file_name != None:
output_file_name = output_file_name
else:
output_file_name = "generated_centerline.nii.gz"
os.rename(fname_output, output_file_name)
path_binary, file_binary, ext_binary = sct.extract_fname(output_file_name)
os.rename("concatenation_file_centerline.txt", file_binary + ".txt")
# Process for a binary file as output:
sct.run("cp " + output_file_name + " ../")
# Process for a text file as output:
sct.run("cp " + file_binary + ".txt" + " ../")
os.chdir("../")
# Remove temporary files
if remove_temp_files:
print ("\nRemove temporary files...")
sct.run("rm -rf " + path_tmp, error_exit="warning")
def main(list_file,
param,
output_file_name=None,
remove_temp_files=1,
verbose=0):
path, file, ext = sct.extract_fname(list_file[0])
# create temporary folder
path_tmp = 'tmp.' + time.strftime("%y%m%d%H%M%S")
sct.run('mkdir ' + path_tmp)
# copy files into tmp folder
sct.printv('\nCopy files into tmp folder...', verbose)
for i in range(len(list_file)):
file_temp = os.path.abspath(list_file[i])
sct.run('cp ' + file_temp + ' ' + path_tmp)
# go to tmp folder
os.chdir(path_tmp)
## Concatenation of the files
# Concatenation : sum of matrices
file_0 = load(file + ext)
data_concatenation = file_0.get_data()
hdr_0 = file_0.get_header()
orientation_file_0 = get_orientation(list_file[0])
if len(list_file) > 0:
for i in range(1, len(list_file)):
orientation_file_temp = get_orientation(list_file[i])
if orientation_file_0 != orientation_file_temp:
print "ERROR: The files ", list_file[0], " and ", list_file[
i], " are not in the same orientation. Use sct_orientation to change the orientation of a file."
sys.exit(2)
file_temp = load(list_file[i])
data_temp = file_temp.get_data()
data_concatenation = data_concatenation + data_temp
# Save concatenation as a file
print '\nWrite NIFTI volumes...'
img = Nifti1Image(data_concatenation, None, hdr_0)
save(img, 'concatenation_file.nii.gz')
# Applying nurbs to the concatenation and save file as binary file
fname_output = extract_centerline('concatenation_file.nii.gz',
remove_temp_files=remove_temp_files,
verbose=verbose,
algo_fitting=param.algo_fitting,
type_window=param.type_window,
window_length=param.window_length)
# Rename files after processing
if output_file_name != None:
output_file_name = output_file_name
else:
output_file_name = "generated_centerline.nii.gz"
os.rename(fname_output, output_file_name)
path_binary, file_binary, ext_binary = sct.extract_fname(output_file_name)
os.rename('concatenation_file_centerline.txt', file_binary + '.txt')
# Process for a binary file as output:
sct.run('cp ' + output_file_name + ' ../')
# Process for a text file as output:
sct.run('cp ' + file_binary + '.txt' + ' ../')
os.chdir('../')
# Remove temporary files
if remove_temp_files:
print('\nRemove temporary files...')
sct.run('rm -rf ' + path_tmp)
def find_centerline(algo, image_fname, path_sct, contrast_type, brain_bool,
folder_output, remove_temp_files, centerline_fname):
if Image(image_fname).dim[2] == 1: # isct_spine_detect requires nz > 1
from sct_image import concat_data
im_concat = concat_data([image_fname, image_fname], dim=2)
im_concat.save(sct.add_suffix(image_fname, '_concat'))
image_fname = sct.add_suffix(image_fname, '_concat')
bool_2d = True
else:
bool_2d = False
if algo == 'svm':
# run optic on a heatmap computed by a trained SVM+HoG algorithm
optic_models_fname = os.path.join(path_sct, 'data', 'optic_models',
'{}_model'.format(contrast_type))
_, centerline_filename = optic.detect_centerline(
image_fname=image_fname,
contrast_type=contrast_type,
optic_models_path=optic_models_fname,
folder_output=folder_output,
remove_temp_files=remove_temp_files,
output_roi=False,
verbose=0)
elif algo == 'cnn':
# CNN parameters
dct_patch_ctr = {
't2': {
'size': (80, 80),
'mean': 51.1417,
'std': 57.4408
},
't2s': {
'size': (80, 80),
'mean': 68.8591,
'std': 71.4659
},
't1': {
'size': (80, 80),
'mean': 55.7359,
'std': 64.3149
},
'dwi': {
'size': (80, 80),
'mean': 55.744,
'std': 45.003
}
}
dct_params_ctr = {
't2': {
'features': 16,
'dilation_layers': 2
},
't2s': {
'features': 8,
'dilation_layers': 3
},
't1': {
'features': 24,
'dilation_layers': 3
},
'dwi': {
'features': 8,
'dilation_layers': 2
}
}
# load model
ctr_model_fname = os.path.join(path_sct, 'data', 'deepseg_sc_models',
'{}_ctr.h5'.format(contrast_type))
ctr_model = nn_architecture_ctr(
height=dct_patch_ctr[contrast_type]['size'][0],
width=dct_patch_ctr[contrast_type]['size'][1],
channels=1,
classes=1,
features=dct_params_ctr[contrast_type]['features'],
depth=2,
temperature=1.0,
padding='same',
batchnorm=True,
dropout=0.0,
dilation_layers=dct_params_ctr[contrast_type]['dilation_layers'])
ctr_model.load_weights(ctr_model_fname)
# compute the heatmap
fname_heatmap = sct.add_suffix(image_fname, "_heatmap")
img_filename = ''.join(sct.extract_fname(fname_heatmap)[:2])
fname_heatmap_nii = img_filename + '.nii'
z_max = heatmap(filename_in=image_fname,
filename_out=fname_heatmap_nii,
model=ctr_model,
patch_shape=dct_patch_ctr[contrast_type]['size'],
mean_train=dct_patch_ctr[contrast_type]['mean'],
std_train=dct_patch_ctr[contrast_type]['std'],
brain_bool=brain_bool)
# run optic on the heatmap
centerline_filename = sct.add_suffix(fname_heatmap, "_ctr")
heatmap2optic(fname_heatmap=fname_heatmap_nii,
lambda_value=7 if contrast_type == 't2s' else 1,
fname_out=centerline_filename,
z_max=z_max if brain_bool else None)
elif algo == 'viewer':
centerline_filename = sct.add_suffix(image_fname, "_ctr")
fname_labels_viewer = _call_viewer_centerline(fname_in=image_fname)
centerline_filename = extract_centerline(fname_labels_viewer,
remove_temp_files=True,
algo_fitting='nurbs',
nurbs_pts_number=8000)
elif algo == 'manual':
centerline_filename = sct.add_suffix(image_fname, "_ctr")
image_manual_centerline = Image(centerline_fname)
# Re-orient and Re-sample the manual centerline
image_centerline_reoriented = msct_image.change_orientation(
image_manual_centerline, 'RPI').save(centerline_filename)
input_resolution = image_centerline_reoriented.dim[4:7]
new_resolution = 'x'.join(['0.5', '0.5', str(input_resolution[2])])
spinalcordtoolbox.resample.nipy_resample.resample_file(
centerline_filename,
centerline_filename,
new_resolution,
'mm',
'linear',
verbose=0)
else:
sct.log.error(
'The parameter "-centerline" is incorrect. Please try again.')
sys.exit(1)
if bool_2d:
from sct_image import split_data
im_split_lst = split_data(Image(centerline_filename), dim=2)
im_split_lst[0].save(centerline_filename)
return centerline_filename
def main(list_file, param, output_file_name=None, remove_temp_files = 1, verbose = 0):
path, file, ext = sct.extract_fname(list_file[0])
# create temporary folder
path_tmp = 'tmp.'+time.strftime("%y%m%d%H%M%S")
sct.run('mkdir '+path_tmp)
# copy files into tmp folder
sct.printv('\nCopy files into tmp folder...', verbose)
for i in range(len(list_file)):
file_temp = os.path.abspath(list_file[i])
sct.run('cp '+file_temp+' '+path_tmp)
# go to tmp folder
os.chdir(path_tmp)
## Concatenation of the files
# Concatenation : sum of matrices
file_0 = load(file+ext)
data_concatenation = file_0.get_data()
hdr_0 = file_0.get_header()
orientation_file_0 = get_orientation(list_file[0])
if len(list_file)>0:
for i in range(1, len(list_file)):
orientation_file_temp = get_orientation(list_file[i])
if orientation_file_0 != orientation_file_temp :
print "ERROR: The files ", list_file[0], " and ", list_file[i], " are not in the same orientation. Use sct_orientation to change the orientation of a file."
sys.exit(2)
file_temp = load(list_file[i])
data_temp = file_temp.get_data()
data_concatenation = data_concatenation + data_temp
# Save concatenation as a file
print '\nWrite NIFTI volumes...'
img = Nifti1Image(data_concatenation, None, hdr_0)
save(img,'concatenation_file.nii.gz')
# Applying nurbs to the concatenation and save file as binary file
fname_output = extract_centerline('concatenation_file.nii.gz', remove_temp_files = remove_temp_files, verbose = verbose, algo_fitting=param.algo_fitting, type_window=param.type_window, window_length=param.window_length)
# Rename files after processing
if output_file_name != None:
output_file_name = output_file_name
else : output_file_name = "generated_centerline.nii.gz"
os.rename(fname_output, output_file_name)
path_binary, file_binary, ext_binary = sct.extract_fname(output_file_name)
os.rename('concatenation_file_centerline.txt', file_binary+'.txt')
# Process for a binary file as output:
sct.run('cp '+output_file_name+' ../')
# Process for a text file as output:
sct.run('cp '+file_binary+ '.txt'+ ' ../')
os.chdir('../')
# Remove temporary files
if remove_temp_files:
print('\nRemove temporary files...')
sct.run('rm -rf '+path_tmp)
def get_centerline_from_labels(fname_in, list_fname_labels, param, output_file_name=None, remove_temp_files=1, verbose=0):
path, file, ext = sct.extract_fname(fname_in)
# create temporary folder
path_tmp = sct.slash_at_the_end('tmp.'+strftime('%y%m%d%H%M%S'), 1)
sct.run('mkdir '+path_tmp)
# Copying input data to tmp folder
sct.printv('\nCopying input data to tmp folder...', verbose)
sct.run('sct_convert -i '+fname_in+' -o '+path_tmp+'data.nii')
file_labels = []
for i in range(len(list_fname_labels)):
file_labels.append('labels_'+str(i)+'.nii.gz')
sct.run('sct_convert -i '+list_fname_labels[i]+' -o '+path_tmp+file_labels[i])
# go to tmp folder
os.chdir(path_tmp)
## Concatenation of the files
# Concatenation : sum of matrices
file_0 = Image('data.nii')
data_concatenation = file_0.data
hdr_0 = file_0.hdr
orientation_file_0 = get_orientation(file_0)
if len(list_fname_labels) > 0:
for i in range(0, len(list_fname_labels)):
orientation_file_temp = get_orientation(file_labels[i], filename=True)
if orientation_file_0 != orientation_file_temp :
print 'ERROR: The files ', fname_in, ' and ', file_labels[i], ' are not in the same orientation. Use sct_image -setorient to change the orientation of a file.'
sys.exit(2)
file_temp = load(file_labels[i])
data_temp = file_temp.get_data()
data_concatenation = data_concatenation + data_temp
# Save concatenation as a file
print '\nWrite NIFTI volumes...'
img = Nifti1Image(data_concatenation, None, hdr_0)
save(img, 'concatenation_file.nii.gz')
# Applying nurbs to the concatenation and save file as binary file
fname_output = extract_centerline('concatenation_file.nii.gz', remove_temp_files = remove_temp_files, verbose = verbose, algo_fitting=param.algo_fitting, type_window=param.type_window, window_length=param.window_length)
# Rename files after processing
if output_file_name != None:
output_file_name = output_file_name
else : output_file_name = 'generated_centerline.nii.gz'
os.rename(fname_output, output_file_name)
path_binary, file_binary, ext_binary = sct.extract_fname(output_file_name)
os.rename('concatenation_file_centerline.txt', file_binary+'.txt')
# Process for a binary file as output:
sct.run('cp '+output_file_name+' ../')
# Process for a text file as output:
sct.run('cp '+file_binary+ '.txt'+ ' ../')
os.chdir('../')
# Remove temporary files
if remove_temp_files:
print('\nRemove temporary files...')
sct.run('rm -rf '+path_tmp)
