def methods_02_lpa( input_dir, verbose ):
cenc_dirs = cenc.directories( input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
util.mkcd_dir( [ cenc_dirs['wmlesions']['dirs']['lpa'] ], True)
util.copy_inputs( [ os.path.join( cenc_dirs['wmlesions']['dirs']['register'], 't2flair_Affine_nu__t2flair_Warped.nii.gz') ],
cenc_dirs['wmlesions']['dirs']['lpa'] )
glob_files = glob.glob('*.gz')
for ii in glob_files:
os.system('gunzip ' + ii)
os.chmod( str.replace(ii, '.gz',''), stat.S_IRUSR | stat.S_IRGRP | stat.S_IWUSR | stat.S_IWGRP)
# Run Matlab
matlab_run_command = "ps_LST_lpa('" + os.path.join( cenc_dirs['wmlesions']['dirs']['lpa'], 't2flair_Affine_nu__t2flair_Warped.nii') + "',''); exit;"
command = [ 'matlab', '-nojvm', '-nosplash', '-nodesktop', '-r', matlab_run_command ]
util.iw_subprocess( command, verbose, verbose, False)
os.chdir(cenc_dirs['wmlesions']['dirs']['lpa'])
for ii in glob.glob('*.nii'):
os.system('gzip ' + ii)
os.chmod( str.replace(ii, '.nii','.nii.gz'), stat.S_IRUSR | stat.S_IRGRP | stat.S_IWUSR | stat.S_IWGRP)
def ants_register(input_file):
# antsRegistration call:
#--------------------------------------------------------------------------------------
if False:
# I am having problems callling the interface. Same problem of bad interface.
command = ['antsRegistration', '--dimensionality', 3, '--float', 0,
'--output', '[', 'mt_Affine_nu__' + input_file +'_,',
'mt_Affine_nu__' + input_file + '_Warped.nii.gz,',
'mt_Affine_nu__' + input_file + '_InverseWarped.nii.gz', ']',
'--interpolation', 'Linear',
'--use-histogram-matching', 0,
'--winsorize-image-intensities', [0.005,0.995],
'--initial-moving-transform', '[', 'nu.nii.gz,' + input_file + '.nii.gz,', 1, ']',
'--transform', 'Rigid[0.1]',
'--metric', 'MI[nu.nii.gz,mt_m1.nii.gz,1,32,Regular,0.25]',
'--convergence', '[1000x500x250x0,1e-6,10]',
'--shrink-factors', '8x4x2x1',
'--smoothing-sigmas', '3x2x1x0vox',
'--transform', 'Affine[0.1]',
'--metric', 'MI[nu.nii.gz,' + input_file + '.nii.gz,1,32,Regular,0.25]',
'--convergence', '[1000x500x250x0,1e-6,10]',
'--shrink-factors', '8x4x2x1',
'--smoothing-sigmas', '3x2x1x0vox'
]
#--------------------------------------------------------------------------------------
# I am having problems callling the interface. Same problem of bad interface.
if False:
reg = Registration()
reg.inputs.fixed_image = 'nu.nii.gz'
reg.inputs.moving_image = input_file + '.nii.gz'
reg.inputs.output_transform_prefix = "t2flair_Affine_nu__" + input_file + "_"
reg.inputs.transforms = ['Affine']
reg.inputs.transform_parameters = [(2.0,), (0.25, 3.0, 0.0)]
reg.inputs.number_of_iterations = [[1000,500,200,100]]
reg.inputs.dimension = 3
reg.inputs.write_composite_transform = False
reg.inputs.collapse_output_transforms = False
reg.inputs.initialize_transforms_per_stage = False
reg.inputs.metric = ['MI']
reg.inputs.metric_weight = [1]
reg.inputs.radius_or_number_of_bins = [32]
reg.inputs.sampling_strategy = ['Random']
reg.inputs.sampling_percentage = [0.05]
reg.inputs.convergence_threshold = [1.e-10]
reg.inputs.convergence_window_size = [10]
reg.inputs.smoothing_sigmas = [[3,2,1,0]]
reg.inputs.sigma_units = ['vox']
reg.inputs.shrink_factors = [[8,4,2,1]]
reg.inputs.use_estimate_learning_rate_once = [True]
reg.inputs.use_histogram_matching = [True] # This is the default
reg.inputs.output_warped_image = 't2flair_Affine_nu__' + input_file + '.nii.gz'
reg.inputs.terminal_output='stream'
print(reg.cmdline)
# reg.run()
# This simple command appears to work.
command = ['antsRegistrationSyNQuick.sh', '-d', '3', '-m', input_file + '.nii.gz', '-r', 'nu.nii.gz',
'-f', 'nu.nii.gz', '-t', 'a', '-o', 't2flair_Affine_nu__' + input_file + '_'
]
util.iw_subprocess( command, True, True, False)
return
def methods_03_stats(input_dir, lower_threshold=0.5, upper_threshold=numpy.inf, min_lesion_volume_voxels=10, verbose=False):
cenc_dirs = cenc.directories(input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
util.mkcd_dir([cenc_dirs['wmlesions']['dirs']['stats']], True)
wm_lesions_stats_filename = os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.csv')
wm_lesions_pmap_stats_filename = os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_pmap.csv')
# Mask LPA Probability Mask and remove NaN
command = [['fslmaths', os.path.join(cenc_dirs['wmlesions']['dirs']['lpa'], 'ples_lpa_mt2flair_Affine_nu__t2flair_Warped.nii.gz'),
'-mas', os.path.join(cenc_dirs['wmlesions']['dirs']['input'], 'mask.nii.gz'), '-nan',
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_pmap.nii.gz')
]]
for ii in command:
util.iw_subprocess(ii, verbose, verbose, False)
# Create labels file from LPA probability map
labels.label_connected_components( os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_pmap.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.nii.gz'),
lower_threshold, upper_threshold )
# Measure properties of labels
labels.properties(os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.nii.gz'),
None, False, ['volume_mm3'],
wm_lesions_stats_filename,
limits_volume_voxels=[min_lesion_volume_voxels, numpy.inf],
limits_bb_volume_voxels=[0, numpy.inf], limits_fill_factor=[0, 1], sort='volume_mm3',
verbose=verbose, verbose_nlines=20)
# Keep labels greater than 10 mm^3. Limit is set above
labels.keep(os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.nii.gz'),
[],
wm_lesions_stats_filename,
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.nii.gz')
)
# 1) Create a WM Lesions mask
# 2) Mask LPA Registered T2 FLAIR
command = [ ['fslmaths', os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.nii.gz'),
'-bin', os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_mask.nii.gz')
],
['fslmaths',
os.path.join(cenc_dirs['wmlesions']['dirs']['lpa'], 'mt2flair_Affine_nu__t2flair_Warped.nii.gz'),
'-mas', os.path.join(cenc_dirs['wmlesions']['dirs']['input'], 'mask.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_t2flair.nii.gz')
]
]
for ii in command:
util.iw_subprocess(ii, verbose, verbose, False)
# Measure Pmaps stats labels
df_pmap_measure = labels.measure( os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_pmap.nii.gz'))
df_pmap_measure.to_csv(wm_lesions_pmap_stats_filename, index=False)
# Write out JSON file with RedCap Instrument
methods_write_json_redcap_instrument(input_dir, wm_lesions_stats_filename, wm_lesions_pmap_stats_filename, verbose)