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FIX: DTITK nonlinear workflow origin reslicing #2561

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Merged
merged 10 commits into from
May 24, 2018
Merged

FIX: DTITK nonlinear workflow origin reslicing #2561

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284f0dd
Merge branch 'master' of https://github.com/nipy/nipype
kesshijordan Apr 10, 2018
ebe82a4
Merge branch 'master' of https://github.com/nipy/nipype
kesshijordan Apr 16, 2018
6db39fd
Merge branch 'master' of https://github.com/nipy/nipype
kesshijordan Apr 29, 2018
5407f0a
moved origins to zero prior to any reslicing (this avoids a problem p…
kesshijordan Apr 29, 2018
ac3286d
reslice output image to match input fixed
kesshijordan May 16, 2018
5d238c0
added apply_xfm workflow
kesshijordan May 23, 2018
73abfda
nonlinear wf works with nonzero origin images
kesshijordan May 23, 2018
5037c40
Merge branch 'master' of https://github.com/kesshijordan/nipype into …
kesshijordan May 24, 2018
fe3c97e
specs
kesshijordan May 24, 2018
9545859
removed non-functional wf
kesshijordan May 24, 2018
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2 changes: 1 addition & 1 deletion nipype/interfaces/dcm2nii.py
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Original file line number Diff line number Diff line change
Expand Up @@ -264,7 +264,7 @@ class Dcm2niixInputSpec(CommandLineInputSpec):
position=-1,
copyfile=False,
mandatory=True,
desc=('A set of filenames to be converted. Note that the current '
desc=('A set of filenames to be converted. Note that the current '
'version (1.0.20180328) of dcm2niix converts any files in the '
'directory. To only convert specific files they should be in an '
'isolated directory'),
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2 changes: 1 addition & 1 deletion nipype/tests/test_nipype.py
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Expand Up @@ -12,7 +12,7 @@ def test_nipype_info():
assert exception_not_raised


@pytest.mark.skipif(not get_nipype_gitversion(),
@pytest.mark.skipif(not get_nipype_gitversion(),
reason="not able to get version from get_nipype_gitversion")
def test_git_hash():
# removing the first "g" from gitversion
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29 changes: 23 additions & 6 deletions nipype/workflows/dmri/dtitk/tensor_registration.py
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Expand Up @@ -52,10 +52,11 @@ def diffeomorphic_tensor_pipeline(name='DiffeoTen',
params={'array_size': (128, 128, 64)}):
"""
Workflow that performs a diffeomorphic registration
(Rigid and Affine follwed by Diffeomorphic)
(Rigid and Affine followed by Diffeomorphic)
Note: the requirements for a diffeomorphic registration specify that
the dimension 0 is a power of 2 so images are resliced prior to
registration
registration. Remember to move origin and reslice prior to applying xfm to
another file!

Example
-------
Expand All @@ -75,7 +76,9 @@ def diffeomorphic_tensor_pipeline(name='DiffeoTen',
fields=['out_file', 'out_file_xfm',
'fixed_resliced', 'moving_resliced']),
name='outputnode')

origin_node_fixed = pe.Node(dtitk.TVAdjustVoxSp(origin=(0, 0, 0)),
name='origin_node_fixed')
origin_node_moving = origin_node_fixed.clone(name='origin_node_moving')
reslice_node_pow2 = pe.Node(dtitk.TVResample(
origin=(0, 0, 0),
array_size=params['array_size']),
Expand All @@ -92,14 +95,23 @@ def diffeomorphic_tensor_pipeline(name='DiffeoTen',
compose_xfm_node = pe.Node(dtitk.ComposeXfm(), name='compose_xfm_node')
apply_xfm_node = pe.Node(dtitk.DiffeoSymTensor3DVol(),
name='apply_xfm_node')
adjust_vs_node_to_input = pe.Node(dtitk.TVAdjustVoxSp(),
name='adjust_vs_node_to_input')
reslice_node_to_input = pe.Node(dtitk.TVResample(),
name='reslice_node_to_input')
input_fa = pe.Node(dtitk.TVtool(in_flag='fa'), name='input_fa')

wf = pe.Workflow(name=name)

# calculate input FA image for origin reference
wf.connect(inputnode, 'fixed_file', input_fa, 'in_file')
# Reslice input images
wf.connect(inputnode, 'fixed_file', reslice_node_pow2, 'in_file')
wf.connect(inputnode, 'fixed_file', origin_node_fixed, 'in_file')
wf.connect(origin_node_fixed, 'out_file', reslice_node_pow2, 'in_file')
wf.connect(reslice_node_pow2, 'out_file',
reslice_node_moving, 'target_file')
wf.connect(inputnode, 'moving_file', reslice_node_moving, 'in_file')
wf.connect(inputnode, 'moving_file', origin_node_moving, 'in_file')
wf.connect(origin_node_moving, 'out_file', reslice_node_moving, 'in_file')
# Rigid registration
wf.connect(reslice_node_pow2, 'out_file', rigid_node, 'fixed_file')
wf.connect(reslice_node_moving, 'out_file', rigid_node, 'moving_file')
Expand All @@ -118,8 +130,13 @@ def diffeomorphic_tensor_pipeline(name='DiffeoTen',
# Apply transform
wf.connect(reslice_node_moving, 'out_file', apply_xfm_node, 'in_file')
wf.connect(compose_xfm_node, 'out_file', apply_xfm_node, 'transform')
# Move origin and reslice to match original fixed input image
wf.connect(apply_xfm_node, 'out_file', adjust_vs_node_to_input, 'in_file')
wf.connect(input_fa, 'out_file', adjust_vs_node_to_input, 'target_file')
wf.connect(adjust_vs_node_to_input, 'out_file', reslice_node_to_input, 'in_file')
wf.connect(input_fa, 'out_file', reslice_node_to_input, 'target_file')
# Send to output
wf.connect(apply_xfm_node, 'out_file', outputnode, 'out_file')
wf.connect(reslice_node_to_input, 'out_file', outputnode, 'out_file')
wf.connect(compose_xfm_node, 'out_file', outputnode, 'out_file_xfm')
wf.connect(reslice_node_pow2, 'out_file', outputnode, 'fixed_resliced')
wf.connect(reslice_node_moving, 'out_file', outputnode, 'moving_resliced')
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2 changes: 1 addition & 1 deletion tools/checkspecs.py
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Expand Up @@ -287,7 +287,7 @@ def test_specs(self, uri):
and "requires" not in trait.__dict__\
and "xor" not in trait.__dict__:
if trait.trait_type.__class__.__name__ is "Range"\
and trait.default == trait.trait_type._low:
and trait.default == trait.trait_type._low:
continue
bad_specs.append(
[uri, c, 'Inputs', traitname, 'default value is set, no value for usedefault'])
Expand Down