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Bug fix rotate bvec #543

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Merged
merged 2 commits into from
Apr 2, 2013
Merged

Bug fix rotate bvec #543

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61b46f9
Modified create_dmri_preprocessing to allow for pipeline use with and…
steelec Mar 27, 2013
660a0da
Fixed error in _rotate_bvec that was adding an extra entry to the out…
steelec Apr 2, 2013
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56 changes: 40 additions & 16 deletions nipype/workflows/dmri/fsl/dti.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,11 +13,10 @@ def transpose(samples_over_fibres):
a = a.reshape(-1, 1)
return a.T.tolist()


def create_dmri_preprocessing(name="dMRI_preprocessing", fieldmap_registration=False):
def create_dmri_preprocessing(name="dMRI_preprocessing", use_fieldmap=True, fieldmap_registration=False):
"""Creates a workflow that chains the necessary pipelines to
correct for motion, eddy currents, and susceptibility
artifacts in EPI dMRI sequences.
correct for motion, eddy currents, and, if selected, susceptibility
artifacts in EPI dMRI sequences.

.. warning::

Expand Down Expand Up @@ -63,9 +62,9 @@ def create_dmri_preprocessing(name="dMRI_preprocessing", fieldmap_registration=F


Optional arguments::

use_fieldmap - True if there are fieldmap files that should be used (default True)
fieldmap_registration - True if registration to fieldmap should be performed (default False)


"""

Expand All @@ -83,17 +82,42 @@ def create_dmri_preprocessing(name="dMRI_preprocessing", fieldmap_registration=F

motion = create_motion_correct_pipeline()
eddy = create_eddy_correct_pipeline()
susceptibility = create_susceptibility_correct_pipeline(

if use_fieldmap: # we have a fieldmap, so lets use it (yay!)
susceptibility = create_susceptibility_correct_pipeline(
fieldmap_registration=fieldmap_registration)

pipeline.connect([
(inputnode, motion, [('in_file', 'inputnode.in_file'), (
'in_bvec', 'inputnode.in_bvec'), ('ref_num', 'inputnode.ref_num')]), (inputnode, eddy, [('ref_num', 'inputnode.ref_num')]), (motion, eddy, [('outputnode.motion_corrected', 'inputnode.in_file')]), (eddy, susceptibility, [('outputnode.eddy_corrected', 'inputnode.in_file')]), (inputnode, susceptibility, [('ref_num', 'inputnode.ref_num'), ('fieldmap_mag', 'inputnode.fieldmap_mag'), ('fieldmap_pha', 'inputnode.fieldmap_pha'), ('te_diff', 'inputnode.te_diff'), ('epi_echospacing', 'inputnode.epi_echospacing'), ('epi_rev_encoding', 'inputnode.epi_rev_encoding'), ('pi_accel_factor', 'inputnode.pi_accel_factor'), ('vsm_sigma', 'inputnode.vsm_sigma')]), (motion, outputnode, [('outputnode.out_bvec', 'bvec_rotated')]), (susceptibility, outputnode, [('outputnode.epi_corrected', 'dmri_corrected')])
])

pipeline.connect([
(inputnode, motion, [('in_file', 'inputnode.in_file'),
('in_bvec', 'inputnode.in_bvec'),
('ref_num', 'inputnode.ref_num')]),
(inputnode, eddy, [('ref_num', 'inputnode.ref_num')]),
(motion, eddy, [('outputnode.motion_corrected', 'inputnode.in_file')]),
(eddy, susceptibility, [('outputnode.eddy_corrected', 'inputnode.in_file')]),
(inputnode, susceptibility, [('ref_num', 'inputnode.ref_num'),
('fieldmap_mag', 'inputnode.fieldmap_mag'),
('fieldmap_pha', 'inputnode.fieldmap_pha'),
('te_diff', 'inputnode.te_diff'),
('epi_echospacing', 'inputnode.epi_echospacing'),
('epi_rev_encoding', 'inputnode.epi_rev_encoding'),
('pi_accel_factor', 'inputnode.pi_accel_factor'),
('vsm_sigma', 'inputnode.vsm_sigma')]),
(motion, outputnode, [('outputnode.out_bvec', 'bvec_rotated')]),
(susceptibility, outputnode, [('outputnode.epi_corrected', 'dmri_corrected')])
])
else: # we don't have a fieldmap, so we just carry on without it :(
pipeline.connect([
(inputnode, motion, [('in_file', 'inputnode.in_file'),
('in_bvec', 'inputnode.in_bvec'),
('ref_num', 'inputnode.ref_num')]),
(inputnode, eddy, [('ref_num', 'inputnode.ref_num')]),
(motion, eddy, [('outputnode.motion_corrected', 'inputnode.in_file')]),
(motion, outputnode, [('outputnode.out_bvec', 'bvec_rotated')]),
(eddy, outputnode, [('outputnode.eddy_corrected', 'dmri_corrected')])
])

return pipeline


def create_bedpostx_pipeline(name="bedpostx"):
"""Creates a pipeline that does the same as bedpostx script from FSL -
calculates diffusion model parameters (distributions not MLE) voxelwise for
Expand Down Expand Up @@ -530,12 +554,12 @@ def _rotate_bvecs(in_bvec, in_matrix):
name, _ = os.path.splitext(name)
out_file = os.path.abspath('./%s_rotated.bvec' % name)
bvecs = np.loadtxt(in_bvec)
new_bvecs = [bvecs[:, 0]]
new_bvecs = np.zeros(shape=bvecs.T.shape) #pre-initialise array, 3 col format

for i, vol_matrix in enumerate(in_matrix[1::]):
for i, vol_matrix in enumerate(in_matrix[0::]): #start index at 0
bvec = np.matrix(bvecs[:, i])
rot = np.matrix(np.loadtxt(vol_matrix)[0:3, 0:3])
new_bvecs.append((np.array(rot * bvec.T).T)[0])
new_bvecs[i] = (np.array(rot * bvec.T).T)[0] #fill each volume with x,y,z as we go along
np.savetxt(out_file, np.array(new_bvecs).T, fmt='%0.15f')
return out_file

Expand Down