def _generate_report(self):
"""Generate the visual report."""
from nilearn.image import threshold_img, load_img
from nilearn.masking import apply_mask, unmask
from niworkflows.viz.utils import plot_registration
NIWORKFLOWS_LOG.info("Generating visual report")
fixed_image_nii = load_img(self._fixed_image)
moving_image_nii = load_img(self._moving_image)
contour_nii = load_img(
self._contour) if self._contour is not None else None
if self._fixed_image_mask:
fixed_image_nii = unmask(
apply_mask(fixed_image_nii, self._fixed_image_mask),
self._fixed_image_mask,
)
# since the moving image is already in the fixed image space we
# should apply the same mask
moving_image_nii = unmask(
apply_mask(moving_image_nii, self._fixed_image_mask),
self._fixed_image_mask,
)
mask_nii = load_img(self._fixed_image_mask)
else:
mask_nii = threshold_img(fixed_image_nii, 1e-3)
n_cuts = 7
if not self._fixed_image_mask and contour_nii:
cuts = cuts_from_bbox(contour_nii, cuts=n_cuts)
else:
cuts = cuts_from_bbox(mask_nii, cuts=n_cuts)
# Call composer
compose_view(
plot_registration(
fixed_image_nii,
"fixed-image",
estimate_brightness=True,
cuts=cuts,
label=self._fixed_image_label,
contour=contour_nii,
compress=self.inputs.compress_report,
dismiss_affine=self._dismiss_affine,
),
plot_registration(
moving_image_nii,
"moving-image",
estimate_brightness=True,
cuts=cuts,
label=self._moving_image_label,
contour=contour_nii,
compress=self.inputs.compress_report,
dismiss_affine=self._dismiss_affine,
),
out_file=self._out_report,
)
def _generate_report(self):
""" Generates the visual report """
from niworkflows.viz.utils import plot_registration
NIWORKFLOWS_LOG.info('Generating visual report')
anat = load_img(self._anat_file)
contour_nii = load_img(self._contour) if self._contour is not None else None
if self._mask_file:
anat = unmask(apply_mask(anat, self._mask_file), self._mask_file)
mask_nii = load_img(self._mask_file)
else:
mask_nii = threshold_img(anat, 1e-3)
n_cuts = 7
if not self._mask_file and contour_nii:
cuts = cuts_from_bbox(contour_nii, cuts=n_cuts)
else:
cuts = cuts_from_bbox(mask_nii, cuts=n_cuts)
# Call composer
compose_view(
plot_registration(anat, 'fixed-image',
estimate_brightness=True,
cuts=cuts,
contour=contour_nii,
compress=self.inputs.compress_report),
[],
out_file=self._out_report
)
def _generate_report(self):
"""Generates the visual report."""
from niworkflows.viz.utils import plot_registration
NIWORKFLOWS_LOG.info("Generating visual report")
anat = load_img(self._anat_file)
contour_nii = load_img(
self._contour) if self._contour is not None else None
if self._mask_file:
anat = unmask(apply_mask(anat, self._mask_file), self._mask_file)
mask_nii = load_img(self._mask_file)
else:
mask_nii = threshold_img(anat, 1e-3)
n_cuts = 7
if not self._mask_file and contour_nii:
cuts = cuts_from_bbox(contour_nii, cuts=n_cuts)
else:
cuts = cuts_from_bbox(mask_nii, cuts=n_cuts)
# Call composer
compose_view(
plot_registration(
anat,
"fixed-image",
estimate_brightness=True,
cuts=cuts,
contour=contour_nii,
compress=self.inputs.compress_report,
),
[],
out_file=self._out_report,
)
def _run_interface(self, runtime):
from niworkflows.viz.utils import (
plot_registration,
cuts_from_bbox,
compose_view,
)
from nibabel import load
rootdir = Path(self.inputs.subjects_dir) / self.inputs.subject_id
_anat_file = str(rootdir / "mri" / "brain.mgz")
_contour_file = str(rootdir / "mri" / "ribbon.mgz")
anat = load(_anat_file)
contour_nii = load(_contour_file)
n_cuts = 7
cuts = cuts_from_bbox(contour_nii, cuts=n_cuts)
self._results["out_report"] = str(Path(runtime.cwd) / self.inputs.out_report)
# Call composer
compose_view(
plot_registration(
anat,
"fixed-image",
estimate_brightness=True,
cuts=cuts,
contour=contour_nii,
compress=self.inputs.compress_report,
),
[],
out_file=self._results["out_report"],
)
return runtime
def _run_interface(self, runtime):
from niworkflows.viz.utils import plot_registration, cuts_from_bbox, compose_view
from nilearn.image import load_img
rootdir = Path(self.inputs.subjects_dir) / self.inputs.subject_id
_anat_file = str(rootdir / 'mri' / 'brain.mgz')
_contour_file = str(rootdir / 'mri' / 'ribbon.mgz')
anat = load_img(_anat_file)
contour_nii = load_img(_contour_file)
n_cuts = 7
cuts = cuts_from_bbox(contour_nii, cuts=n_cuts)
self._results['out_report'] = str(
Path(runtime.cwd) / self.inputs.out_report)
# Call composer
compose_view(plot_registration(anat,
'fixed-image',
estimate_brightness=True,
cuts=cuts,
contour=contour_nii,
compress=self.inputs.compress_report),
[],
out_file=self._results['out_report'])
return runtime
def _generate_report(self):
""" Generates the visual report """
from niworkflows.viz.utils import plot_registration
NIWORKFLOWS_LOG.info('Generating visual report')
fixed_image_nii = load_img(self._fixed_image)
moving_image_nii = load_img(self._moving_image)
contour_nii = load_img(self._contour) if self._contour is not None else None
if self._fixed_image_mask:
fixed_image_nii = unmask(apply_mask(fixed_image_nii,
self._fixed_image_mask),
self._fixed_image_mask)
# since the moving image is already in the fixed image space we
# should apply the same mask
moving_image_nii = unmask(apply_mask(moving_image_nii,
self._fixed_image_mask),
self._fixed_image_mask)
mask_nii = load_img(self._fixed_image_mask)
else:
mask_nii = threshold_img(fixed_image_nii, 1e-3)
n_cuts = 7
if not self._fixed_image_mask and contour_nii:
cuts = cuts_from_bbox(contour_nii, cuts=n_cuts)
else:
cuts = cuts_from_bbox(mask_nii, cuts=n_cuts)
# Call composer
compose_view(
plot_registration(fixed_image_nii, 'fixed-image',
estimate_brightness=True,
cuts=cuts,
label=self._fixed_image_label,
contour=contour_nii,
compress=self.inputs.compress_report),
plot_registration(moving_image_nii, 'moving-image',
estimate_brightness=True,
cuts=cuts,
label=self._moving_image_label,
contour=contour_nii,
compress=self.inputs.compress_report),
out_file=self._out_report
)
def _run_interface(self, runtime):
fixed_img = load_img(self.inputs.fixed_img)
moving_img = load_img(self.inputs.moving_img)
mask = load_img(self.inputs.mask_img)
out_dir = os.path.realpath(self.inputs.out_dir)
cuts = cuts_from_bbox(mask, self.inputs.cuts)
_, fname, _ = split_filename(self.inputs.moving_img)
compose_view(plot_registration(fixed_img,
'fixed-image',
estimate_brightness=True,
cuts=cuts,
label='fixed'),
plot_registration(moving_img,
'moving-image',
estimate_brightness=True,
cuts=cuts,
label='moving'),
out_file=os.path.join(out_dir, (fname + '_vizQC.svg')))
return runtime
def make_registration(*, moving, fixed, mask, out_file):
"""
Creates `out_file`.svg of registration between `moving` and `fixed`
Parameters
----------
moving : str
Path to file that was registered to `fixed`
fixed : str
Path to file that `moving` was registered to
mask : str
Path to brain mask file
out_file : str
Path to where svg will be saved
Returns
-------
out_file : str
Where svg was saved
"""
if not out_file.endswith('.svg'): out_file += '.svg'
cuts = cuts_from_bbox(nib.load(mask), cuts=7)
compose_view(
plot_registration(nib.load(fixed),
'fixed-image',
estimate_brightness=True,
cuts=cuts,
label='fixed'),
plot_registration(nib.load(moving),
'moving-image',
estimate_brightness=True,
cuts=cuts,
label='moving'),
out_file=out_file
)
return out_file