def avgb0_wf(name='AvgB0Workflow'):
"""
Implements workflow to calculate the average of dwi b0 images.
.. workflow::
from mriqc.workflows.diffusion import avgb0_wf
wf = avgb0_wf
"""
workflow = pe.Workflow(name=name)
inputnode = pe.Node(niu.IdentityInterface(
fields=['in_files']),
name='inputnode')
outputnode = pe.Node(niu.IdentityInterface(fields=['out_file']),
name='outputnode')
merge = pe.Node(fsl.Merge(dimension='t'), name='Merge')
avg = pe.Node(fsl.maths.MeanImage(), name='AvgImage')
workflow.connect([
(inputnode, merge, [('in_files', 'in_files')]),
(merge, avg, [('merged_file', 'in_file')]),
(avg, outputnode, [('out_file', 'out_file')])
])
return workflow
def _run_interface(self, runtime):
in_files = self.inputs.in_files
if not isinstance(in_files, list):
in_files = [self.inputs.in_files]
# Generate output average name early
self._results['out_avg'] = genfname(self.inputs.in_files[0],
suffix='avg')
if self.inputs.to_ras:
in_files = [reorient(inf) for inf in in_files]
if len(in_files) == 1:
filenii = nb.load(in_files[0])
filedata = filenii.get_data()
# magnitude files can have an extra dimension empty
if filedata.ndim == 5:
sqdata = np.squeeze(filedata)
if sqdata.ndim == 5:
raise RuntimeError('Input image (%s) is 5D' % in_files[0])
else:
in_files = [genfname(in_files[0], suffix='squeezed')]
nb.Nifti1Image(sqdata, filenii.get_affine(),
filenii.get_header()).to_filename(
in_files[0])
if np.squeeze(nb.load(in_files[0]).get_data()).ndim < 4:
self._results['out_file'] = in_files[0]
self._results['out_avg'] = in_files[0]
# TODO: generate identity out_mats and zero-filled out_movpar
return runtime
in_files = in_files[0]
else:
magmrg = fsl.Merge(dimension='t', in_files=self.inputs.in_files)
in_files = magmrg.run().outputs.merged_file
mcflirt = fsl.MCFLIRT(cost='normcorr',
save_mats=True,
save_plots=True,
ref_vol=0,
in_file=in_files)
mcres = mcflirt.run()
self._results['out_mats'] = mcres.outputs.mat_file
self._results['out_movpar'] = mcres.outputs.par_file
self._results['out_file'] = mcres.outputs.out_file
hmcnii = nb.load(mcres.outputs.out_file)
hmcdat = hmcnii.get_data().mean(axis=3)
if self.inputs.zero_based_avg:
hmcdat -= hmcdat.min()
nb.Nifti1Image(hmcdat, hmcnii.get_affine(),
hmcnii.get_header()).to_filename(
self._results['out_avg'])
return runtime
