def directInvokeAlgorithm(self, vals):
print('oooo invoking: smoothImage with vals', vals)
input = self.inputs['input']
s = (vals['sigma'])
try:
self.outputs['output'] = libbis.gaussianSmoothImageWASM(
input,
paramobj={
"sigmas": [s, s, s],
"inmm": self.parseBoolean(vals['inmm']),
"radiusfactor": vals['radiusfactor'],
},
debug=self.parseBoolean(vals['debug']))
except:
e = sys.exc_info()[0]
print('---- Failed to invoke algorithm', e)
return False
return True
};
matr=np.eye(4,dtype=np.float32);
group_resliced=libbiswasm.resliceImageWASM(group,matr,resl_paramobj,2);
print('++++ \t Group parcellation dims=',group_resliced.dimensions);
if (smooth == 0):
fmri_smoothed = fmri;
print('++++ \t No smoothing required...');
else:
print('++++ \t Smoothing fMRI image...');
c = smooth * 0.4247;
fmri_smoothed = libbiswasm.gaussianSmoothImageWASM(fmri,
paramobj={
"sigmas": [c, c, c],
"inmm": True,
"radiusfactor": 1.5,
}, debug=2);
out_img=libbiswasm.individualizeParcellationWASM(fmri_smoothed,group_resliced,paramobj,2);
out_img.save(output);
print('++++\n Output image is saved in ',output);
output_sm = output.replace('.nii','') + '_sm.nii'
fmri_smoothed.save(output_sm);
sys.exit();
def directInvokeAlgorithm(self, vals):
print('oooo invoking: individualizedParcellation with vals', vals)
debug = self.parseBoolean(vals['debug'])
fmri = self.inputs['fmri']
group = self.inputs['parc']
if (fmri.hasSameOrientation(group, 'fMRI Image', 'Group Parcellation',
True) == False):
return False
fmriDim = fmri.dimensions
groupDim = group.dimensions
# Reslice Group Parcellation if needed
if (fmriDim[0] != groupDim[0] or fmriDim[1] != groupDim[1]
or fmriDim[2] != groupDim[2]):
print(
'++++ \t Group parcellation being resliced to match the fMRI image dimension...'
)
resl_paramobj = {
"interpolation": 0,
"dimensions": fmri.dimensions,
"spacing": fmri.spacing,
"datatype": "short",
"backgroundValue": 0.0,
}
matr = np.eye(4, dtype=np.float32)
try:
print(
'++++ Reslicing group parcellation to match dimensions of individual fmri image'
)
group = libbis.resliceImageWASM(group, matr, resl_paramobj,
debug)
except:
e = sys.exc_info()[0]
print('---- Failed to invoke algorithm', e)
return False
print('++++ \t Group parcellation dims=', group.dimensions)
# Smooth If needed
smooth = vals['smooth']
if (smooth > 0.001):
print('++++ \t Smoothing fMRI image...')
c = smooth * 0.4247
smooth_paramobj = {
"sigmas": [c, c, c],
"inmm": True,
"radiusfactor": 1.5,
"vtkboundary": True,
}
try:
print('++++ Smoothing fmri Image')
fmri = libbis.gaussianSmoothImageWASM(fmri, smooth_paramobj,
debug)
except:
e = sys.exc_info()[0]
print('---- Failed to invoke algorithm', e)
return False
# Actual Parcellation
paramobj = {
'numberofexemplars': vals['numregions'],
'usefloat': self.parseBoolean(vals['usefloat']),
'saveexemplars': self.parseBoolean(vals['saveexemplars']),
}
try:
self.outputs['output'] = libbis.individualizedParcellationWASM(
fmri, group, paramobj, debug)
except:
e = sys.exc_info()[0]
print('---- Failed to invoke algorithm', e)
return False
return True