def checkFirst(prefix, structures): #pylint: disable=unused-variable
import os
from mrtrix3 import app, file, path # pylint: disable=redefined-builtin
vtk_files = [ prefix + '-' + struct + '_first.vtk' for struct in structures ]
existing_file_count = sum([ os.path.exists(filename) for filename in vtk_files ])
if existing_file_count != len(vtk_files):
if 'SGE_ROOT' in os.environ:
app.console('FSL FIRST job has been submitted to SGE; awaiting completion')
app.console('(note however that FIRST may fail silently, and hence this script may hang indefinitely)')
file.waitFor(vtk_files)
else:
app.error('FSL FIRST has failed; only ' + str(existing_file_count) + ' of ' + str(len(vtk_files)) + ' structures were segmented successfully (check ' + path.toTemp('first.logs', False) + ')')
def checkFirst(prefix, structures): #pylint: disable=unused-variable
import os
from mrtrix3 import app, file, path # pylint: disable=redefined-builtin
vtk_files = [prefix + '-' + struct + '_first.vtk' for struct in structures]
existing_file_count = sum(
[os.path.exists(filename) for filename in vtk_files])
if existing_file_count != len(vtk_files):
if 'SGE_ROOT' in os.environ:
app.console(
'FSL FIRST job has been submitted to SGE; awaiting completion')
app.console(
'(note however that FIRST may fail silently, and hence this script may hang indefinitely)'
)
file.waitFor(vtk_files)
else:
app.error('FSL FIRST has failed; only ' +
str(existing_file_count) + ' of ' + str(len(vtk_files)) +
' structures were segmented successfully (check ' +
path.toTemp('first.logs', False) + ')')
def execute():
import os
from distutils.spawn import find_executable
from mrtrix3 import app, file, fsl, image, run
if app.isWindows():
app.error(
'\'fsl\' algorithm of 5ttgen script cannot be run on Windows: FSL not available on Windows'
)
fsl_path = os.environ.get('FSLDIR', '')
if not fsl_path:
app.error(
'Environment variable FSLDIR is not set; please run appropriate FSL configuration script'
)
ssroi_cmd = 'standard_space_roi'
if not find_executable(ssroi_cmd):
ssroi_cmd = 'fsl5.0-standard_space_roi'
if not find_executable(ssroi_cmd):
app.error(
'Could not find FSL program standard_space_roi; please verify FSL install'
)
bet_cmd = 'bet'
if not find_executable(bet_cmd):
bet_cmd = 'fsl5.0-bet'
if not find_executable(bet_cmd):
app.error(
'Could not find FSL program bet; please verify FSL install')
fast_cmd = 'fast'
if not find_executable(fast_cmd):
fast_cmd = 'fsl5.0-fast'
if not find_executable(fast_cmd):
app.error(
'Could not find FSL program fast; please verify FSL install')
first_cmd = 'run_first_all'
if not find_executable(first_cmd):
first_cmd = "fsl5.0-run_first_all"
if not find_executable(first_cmd):
app.error(
'Could not find FSL program run_first_all; please verify FSL install'
)
first_atlas_path = os.path.join(fsl_path, 'data', 'first',
'models_336_bin')
if not os.path.isdir(first_atlas_path):
app.error(
'Atlases required for FSL\'s FIRST program not installed; please install fsl-first-data using your relevant package manager'
)
fsl_suffix = fsl.suffix()
sgm_structures = [
'L_Accu', 'R_Accu', 'L_Caud', 'R_Caud', 'L_Pall', 'R_Pall', 'L_Puta',
'R_Puta', 'L_Thal', 'R_Thal'
]
if app.args.sgm_amyg_hipp:
sgm_structures.extend(['L_Amyg', 'R_Amyg', 'L_Hipp', 'R_Hipp'])
run.command('mrconvert input.mif T1.nii -stride -1,+2,+3')
fast_t1_input = 'T1.nii'
fast_t2_input = ''
# Decide whether or not we're going to do any brain masking
if os.path.exists('mask.mif'):
fast_t1_input = 'T1_masked' + fsl_suffix
# Check to see if the mask matches the T1 image
if image.match('T1.nii', 'mask.mif'):
run.command('mrcalc T1.nii mask.mif -mult ' + fast_t1_input)
mask_path = 'mask.mif'
else:
app.warn('Mask image does not match input image - re-gridding')
run.command(
'mrtransform mask.mif mask_regrid.mif -template T1.nii')
run.command('mrcalc T1.nii mask_regrid.mif ' + fast_t1_input)
mask_path = 'mask_regrid.mif'
if os.path.exists('T2.nii'):
fast_t2_input = 'T2_masked' + fsl_suffix
run.command('mrcalc T2.nii ' + mask_path + ' -mult ' +
fast_t2_input)
elif app.args.premasked:
fast_t1_input = 'T1.nii'
if os.path.exists('T2.nii'):
fast_t2_input = 'T2.nii'
else:
# Use FSL command standard_space_roi to do an initial masking of the image before BET
# Also reduce the FoV of the image
# Using MNI 1mm dilated brain mask rather than the -b option in standard_space_roi (which uses the 2mm mask); the latter looks 'buggy' to me... Unfortunately even with the 1mm 'dilated' mask, it can still cut into some brain areas, hence the explicit dilation
mni_mask_path = os.path.join(fsl_path, 'data', 'standard',
'MNI152_T1_1mm_brain_mask_dil.nii.gz')
mni_mask_dilation = 0
if os.path.exists(mni_mask_path):
mni_mask_dilation = 4
else:
mni_mask_path = os.path.join(
fsl_path, 'data', 'standard',
'MNI152_T1_2mm_brain_mask_dil.nii.gz')
if os.path.exists(mni_mask_path):
mni_mask_dilation = 2
if mni_mask_dilation:
run.command('maskfilter ' + mni_mask_path +
' dilate mni_mask.nii -npass ' +
str(mni_mask_dilation))
if app.args.nocrop:
ssroi_roi_option = ' -roiNONE'
else:
ssroi_roi_option = ' -roiFOV'
run.command(
ssroi_cmd + ' T1.nii T1_preBET' + fsl_suffix +
' -maskMASK mni_mask.nii' + ssroi_roi_option, False)
else:
run.command(ssroi_cmd + ' T1.nii T1_preBET' + fsl_suffix + ' -b',
False)
# For whatever reason, the output file from standard_space_roi may not be
# completed before BET is run
file.waitFor('T1_preBET' + fsl_suffix)
# BET
fast_t1_input = 'T1_BET' + fsl_suffix
run.command(bet_cmd + ' T1_preBET' + fsl_suffix + ' ' + fast_t1_input +
' -f 0.15 -R')
if os.path.exists('T2.nii'):
if app.args.nocrop:
fast_t2_input = 'T2.nii'
else:
# Just a reduction of FoV, no sub-voxel interpolation going on
run.command('mrtransform T2.nii T2_cropped.nii -template ' +
fast_t1_input + ' -interp nearest')
fast_t2_input = 'T2_cropped.nii'
# Finish branching based on brain masking
# FAST
if fast_t2_input:
run.command(fast_cmd + ' -S 2 ' + fast_t2_input + ' ' + fast_t1_input)
else:
run.command(fast_cmd + ' ' + fast_t1_input)
fast_output_prefix = fast_t1_input.split('.')[0]
# FIRST
first_input_is_brain_extracted = ''
if app.args.premasked:
first_input_is_brain_extracted = ' -b'
run.command(first_cmd + ' -s ' + ','.join(sgm_structures) +
' -i T1.nii -o first' + first_input_is_brain_extracted)
# Test to see whether or not FIRST has succeeded
# However if the expected image is absent, it may be due to FIRST being run
# on SGE; in this case it is necessary to wait and see if the file appears.
# But even in this case, FIRST may still fail, and the file will never appear...
combined_image_path = 'first_all_none_firstseg' + fsl_suffix
if not os.path.isfile(combined_image_path):
if 'SGE_ROOT' in os.environ:
app.console(
'FSL FIRST job has been submitted to SGE; awaiting completion')
app.console(
'(note however that FIRST may fail, and hence this script may hang indefinitely)'
)
file.waitFor(combined_image_path)
else:
app.error(
'FSL FIRST has failed; not all structures were segmented successfully (check '
+ path.toTemp('first.logs', False) + ')')
# Convert FIRST meshes to partial volume images
pve_image_list = []
for struct in sgm_structures:
pve_image_path = 'mesh2pve_' + struct + '.mif'
vtk_in_path = 'first-' + struct + '_first.vtk'
vtk_temp_path = struct + '.vtk'
run.command('meshconvert ' + vtk_in_path + ' ' + vtk_temp_path +
' -transform first2real T1.nii')
run.command('mesh2pve ' + vtk_temp_path + ' ' + fast_t1_input + ' ' +
pve_image_path)
pve_image_list.append(pve_image_path)
pve_cat = ' '.join(pve_image_list)
run.command('mrmath ' + pve_cat +
' sum - | mrcalc - 1.0 -min all_sgms.mif')
# Looks like FAST in 5.0 ignores FSLOUTPUTTYPE when writing the PVE images
# Will have to wait and see whether this changes, and update the script accordingly
if fast_cmd == 'fast':
fast_suffix = fsl_suffix
else:
fast_suffix = '.nii.gz'
# Combine the tissue images into the 5TT format within the script itself
# Step 1: Run LCC on the WM image
run.command(
'mrthreshold ' + fast_output_prefix + '_pve_2' + fast_suffix +
' - -abs 0.001 | maskfilter - connect - -connectivity | mrcalc 1 - 1 -gt -sub remove_unconnected_wm_mask.mif -datatype bit'
)
# Step 2: Generate the images in the same fashion as the 5ttgen command
run.command('mrcalc ' + fast_output_prefix + '_pve_0' + fast_suffix +
' remove_unconnected_wm_mask.mif -mult csf.mif')
run.command('mrcalc 1.0 csf.mif -sub all_sgms.mif -min sgm.mif')
run.command('mrcalc 1.0 csf.mif sgm.mif -add -sub ' + fast_output_prefix +
'_pve_1' + fast_suffix + ' ' + fast_output_prefix + '_pve_2' +
fast_suffix + ' -add -div multiplier.mif')
run.command(
'mrcalc multiplier.mif -finite multiplier.mif 0.0 -if multiplier_noNAN.mif'
)
run.command(
'mrcalc ' + fast_output_prefix + '_pve_1' + fast_suffix +
' multiplier_noNAN.mif -mult remove_unconnected_wm_mask.mif -mult cgm.mif'
)
run.command(
'mrcalc ' + fast_output_prefix + '_pve_2' + fast_suffix +
' multiplier_noNAN.mif -mult remove_unconnected_wm_mask.mif -mult wm.mif'
)
run.command('mrcalc 0 wm.mif -min path.mif')
run.command(
'mrcat cgm.mif sgm.mif wm.mif csf.mif path.mif - -axis 3 | mrconvert - combined_precrop.mif -stride +2,+3,+4,+1'
)
# Use mrcrop to reduce file size (improves caching of image data during tracking)
if app.args.nocrop:
run.command('mrconvert combined_precrop.mif result.mif')
else:
run.command(
'mrmath combined_precrop.mif sum - -axis 3 | mrthreshold - - -abs 0.5 | mrcrop combined_precrop.mif result.mif -mask -'
)