def qc(t1files, wmfiles, asegfiles, whitefiles, pialfiles, annotfiles,
actor_ang=[0., 0., 0.], output_directory=None,
fsconfig="/i2bm/local/freesurfer/SetUpFreeSurfer.sh"):
""" Compute some quality check plots on the converted FrreSurfer
outputs.
The subjecy id in the input files must appear in the -3 position:
xxx/subject_id/convert/t1.nii.gz
Steps:
* t1-images overlays
* 3d surface segmentation snaps
* t1-surfaces overlays
actor_ang: float (optional, default 0)
the actor rotation in the z direction.
<unit>
<input name="t1files" type="List_File" description="The
t1 subject files."/>
<input name="wmfiles" type="List_File" description="The
white matter subject files."/>
<input name="asegfiles" type="List_File" description="The
subcortical segmentation subject files."/>
<input name="output_directory" type="Directory" description="The
conversion destination folder."/>
<input name="whitefiles" type="List_File" description="The subject
cortex surfaces."/>
<input name="pialfiles" type="List_File" description="The subject pial
surfaces."/>
<input name="annotfiles" type="List_File" description="The pial/white
surface annotations."/>
<input name="actor_ang" type="List_Float" description="The actor x, y,
z position (in degrees)."/>
<input name="fsconfig" type="File" description="The freesurfer
configuration batch."/>
<output name="qcfiles" type="List_File" description="The quality check
snaps."/>
</unit>
"""
import clindmri.plot.pvtk as pvtk
from clindmri.plot.slicer import plot_image
# Create a t1 subject map
t1map = {}
for fname in t1files:
subject_id = fname.split("/")[-3]
if subject_id in t1map:
raise Exception("Can't map two t1 for subject '{0}'"
".".format(subject_id))
t1map[subject_id] = fname
# Create the output list that will contain all the qc files
qcfiles = []
# Construct the t1-surfaces overlays and the 3d surface segmentation snaps
ren = pvtk.ren()
for name, files in [("white", whitefiles), ("pial", pialfiles)]:
for fname in files:
# Get the t1 reference image
subject_id = fname.split("/")[-3]
t1file = t1map[subject_id]
t1_image = nibabel.load(t1file)
# Get the qc output directory
qcdir = os.path.join(os.path.dirname(fname), "qc")
qcname = os.path.basename(fname)
if not os.path.isdir(qcdir):
os.makedirs(qcdir)
# Get the triangular mesh
basename = os.path.basename(fname).replace(
name, "aparc.annot").replace(".native", "")
annotfile = os.path.join(os.path.dirname(fname), basename)
if annotfile not in annotfiles:
raise ValueError(
"Annotation file '{0}' can't be found.".format(annotfile))
surface = TriSurface.load(fname, annotfile=annotfile)
# Construct the surfaces binarized volume
binarizedfile = os.path.join(qcdir, qcname + ".nii.gz")
overlay = numpy.zeros(t1_image.shape, dtype=numpy.uint)
indices = numpy.round(surface.vertices).astype(int).T
indices[0, numpy.where(indices[0] >= t1_image.shape[0])] = 0
indices[1, numpy.where(indices[1] >= t1_image.shape[1])] = 0
indices[2, numpy.where(indices[2] >= t1_image.shape[2])] = 0
overlay[indices.tolist()] = 1
overlay_image = nibabel.Nifti1Image(overlay, t1_image.get_affine())
nibabel.save(overlay_image, binarizedfile)
snap_file = os.path.join(qcdir, qcname + ".png")
plot_image(t1file, overlay_file=binarizedfile, snap_file=snap_file,
name=qcname, overlay_cmap="cold_hot")
qcfiles.append(snap_file)
# Create a vtk surface actor of the cortex surface with the
# associated labels
ctab = [item["color"] for _, item in surface.metadata.items()]
actor = pvtk.surface(
surface.vertices, surface.triangles, surface.labels, ctab)
actor.RotateX(actor_ang[0])
actor.RotateY(actor_ang[1])
actor.RotateZ(actor_ang[2])
# Create a 3d surface segmentation snap
pvtk.add(ren, actor)
snaps = pvtk.record(ren, qcdir, qcname, n_frames=36,
az_ang=10, animate=True, delay=50)
qcfiles.append(snaps[0])
snaps = pvtk.record(ren, qcdir, qcname + ".3d", n_frames=1)
qcfiles.append(snaps[0])
pvtk.clear(ren)
# Get the FreeSurfer lookup table
fs_lut_names, fs_lut_colors = parse_fs_lut(os.path.join(
os.path.dirname(fsconfig), "FreeSurferColorLUT.txt"))
cmap = []
nb_values = numpy.asarray(fs_lut_colors.keys()).max()
cmap = numpy.zeros((nb_values, 4), dtype=numpy.single)
for key, color in fs_lut_colors.items():
if key > 0:
cmap[key - 1, :3] = color
cmap[:, 3] = 200.
cmap /= 255.
# Compute t1-images overlays
for name, files in [("aseg", asegfiles), ("wm", wmfiles)]:
for fname in files:
# Get the t1 reference image
subject_id = fname.split("/")[-3]
t1file = t1map[subject_id]
t1_image = nibabel.load(t1file)
# Get the qc output directory
qcdir = os.path.join(os.path.dirname(fname), "qc")
if not os.path.isdir(qcdir):
os.makedirs(qcdir)
# Troncate the color map based on the label max
array = nibabel.load(fname).get_data()
order = sorted(set(array.flatten()))
ccmap = cmap[order[1]: order[-1] + 1]
# Overlay the current image with the t1 image
qcname = "t1-{0}".format(name)
snap_file = os.path.join(qcdir, qcname + ".png")
plot_image(t1file, overlay_file=fname, snap_file=snap_file,
name=qcname, overlay_cmap=ccmap, cut_coords=(0, 0, 0))
qcfiles.append(snap_file)
return qcfiles
if fsdir is None:
raise NotImplementedError()
# recon-all -s 0001 -i T1.nii.gz
if use_vtk:
physical_to_index = numpy.linalg.inv(nibabel.load(t1_file).get_affine())
hemi_surfaces = read_cortex_surface_segmentation(fsdir, physical_to_index)
ren = pvtk.ren()
for hemi in ["lh", "rh"]:
surface = hemi_surfaces[hemi]
ctab = [item["color"] for _, item in surface.metadata.items()]
actor = pvtk.surface(surface.vertices, surface.triangles,
surface.labels, ctab)
pvtk.add(ren, actor)
pvtk.record(ren, qcdir, hemi + "_white")
pvtk.clear(ren)
actor = pvtk.surface(surface.inflated_vertices, surface.triangles,
surface.labels, ctab)
pvtk.add(ren, actor)
pvtk.record(ren, qcdir, hemi + "_inflated")
pvtk.clear(ren)
"""
Diffusion Processing
====================
At this point we have a motion- & artifact-corrected image, the corrected
gradient table and a mask of the non-diffusion-weighted image.
From our DTI data, we need to produce the following information:
if fsdir is None:
raise NotImplementedError()
# recon-all -s 0001 -i T1.nii.gz
if use_vtk:
physical_to_index = numpy.linalg.inv(nibabel.load(t1_file).get_affine())
hemi_surfaces = read_cortex_surface_segmentation(fsdir, physical_to_index)
ren = pvtk.ren()
for hemi in ["lh", "rh"]:
surface = hemi_surfaces[hemi]
ctab = [item["color"] for _, item in surface.metadata.items()]
actor = pvtk.surface(surface.vertices, surface.triangles,
surface.labels, ctab)
pvtk.add(ren, actor)
pvtk.record(ren, qcdir, hemi + "_white")
pvtk.clear(ren)
actor = pvtk.surface(surface.inflated_vertices, surface.triangles,
surface.labels, ctab)
pvtk.add(ren, actor)
pvtk.record(ren, qcdir, hemi + "_inflated")
pvtk.clear(ren)
"""
Diffusion Processing
====================
At this point we have a motion- & artifact-corrected image, the corrected
gradient table and a mask of the non-diffusion-weighted image.
From our DTI data, we need to produce the following information:
* The mask of the non-diffusion-weighted image.
def qc(t1files,
wmfiles,
asegfiles,
whitefiles,
pialfiles,
annotfiles,
actor_ang=[0., 0., 0.],
output_directory=None,
fsconfig="/i2bm/local/freesurfer/SetUpFreeSurfer.sh"):
""" Compute some quality check plots on the converted FrreSurfer
outputs.
The subjecy id in the input files must appear in the -3 position:
xxx/subject_id/convert/t1.nii.gz
Steps:
* t1-images overlays
* 3d surface segmentation snaps
* t1-surfaces overlays
actor_ang: float (optional, default 0)
the actor rotation in the z direction.
<unit>
<input name="t1files" type="List_File" description="The
t1 subject files."/>
<input name="wmfiles" type="List_File" description="The
white matter subject files."/>
<input name="asegfiles" type="List_File" description="The
subcortical segmentation subject files."/>
<input name="output_directory" type="Directory" description="The
conversion destination folder."/>
<input name="whitefiles" type="List_File" description="The subject
cortex surfaces."/>
<input name="pialfiles" type="List_File" description="The subject pial
surfaces."/>
<input name="annotfiles" type="List_File" description="The pial/white
surface annotations."/>
<input name="actor_ang" type="List_Float" description="The actor x, y,
z position (in degrees)."/>
<input name="fsconfig" type="File" description="The freesurfer
configuration batch."/>
<output name="qcfiles" type="List_File" description="The quality check
snaps."/>
</unit>
"""
import clindmri.plot.pvtk as pvtk
from clindmri.plot.slicer import plot_image
# Create a t1 subject map
t1map = {}
for fname in t1files:
subject_id = fname.split("/")[-3]
if subject_id in t1map:
raise Exception("Can't map two t1 for subject '{0}'"
".".format(subject_id))
t1map[subject_id] = fname
# Create the output list that will contain all the qc files
qcfiles = []
# Construct the t1-surfaces overlays and the 3d surface segmentation snaps
ren = pvtk.ren()
for name, files in [("white", whitefiles), ("pial", pialfiles)]:
for fname in files:
# Get the t1 reference image
subject_id = fname.split("/")[-3]
t1file = t1map[subject_id]
t1_image = nibabel.load(t1file)
# Get the qc output directory
qcdir = os.path.join(os.path.dirname(fname), "qc")
qcname = os.path.basename(fname)
if not os.path.isdir(qcdir):
os.makedirs(qcdir)
# Get the triangular mesh
basename = os.path.basename(fname).replace(name,
"aparc.annot").replace(
".native", "")
annotfile = os.path.join(os.path.dirname(fname), basename)
if annotfile not in annotfiles:
raise ValueError(
"Annotation file '{0}' can't be found.".format(annotfile))
surface = TriSurface.load(fname, annotfile=annotfile)
# Construct the surfaces binarized volume
binarizedfile = os.path.join(qcdir, qcname + ".nii.gz")
overlay = numpy.zeros(t1_image.shape, dtype=numpy.uint)
indices = numpy.round(surface.vertices).astype(int).T
indices[0, numpy.where(indices[0] >= t1_image.shape[0])] = 0
indices[1, numpy.where(indices[1] >= t1_image.shape[1])] = 0
indices[2, numpy.where(indices[2] >= t1_image.shape[2])] = 0
overlay[indices.tolist()] = 1
overlay_image = nibabel.Nifti1Image(overlay, t1_image.get_affine())
nibabel.save(overlay_image, binarizedfile)
snap_file = os.path.join(qcdir, qcname + ".png")
plot_image(t1file,
overlay_file=binarizedfile,
snap_file=snap_file,
name=qcname,
overlay_cmap="cold_hot")
qcfiles.append(snap_file)
# Create a vtk surface actor of the cortex surface with the
# associated labels
ctab = [item["color"] for _, item in surface.metadata.items()]
actor = pvtk.surface(surface.vertices, surface.triangles,
surface.labels, ctab)
actor.RotateX(actor_ang[0])
actor.RotateY(actor_ang[1])
actor.RotateZ(actor_ang[2])
# Create a 3d surface segmentation snap
pvtk.add(ren, actor)
snaps = pvtk.record(ren,
qcdir,
qcname,
n_frames=36,
az_ang=10,
animate=True,
delay=50)
qcfiles.append(snaps[0])
snaps = pvtk.record(ren, qcdir, qcname + ".3d", n_frames=1)
qcfiles.append(snaps[0])
pvtk.clear(ren)
# Get the FreeSurfer lookup table
fs_lut_names, fs_lut_colors = parse_fs_lut(
os.path.join(os.path.dirname(fsconfig), "FreeSurferColorLUT.txt"))
cmap = []
nb_values = numpy.asarray(fs_lut_colors.keys()).max()
cmap = numpy.zeros((nb_values, 4), dtype=numpy.single)
for key, color in fs_lut_colors.items():
if key > 0:
cmap[key - 1, :3] = color
cmap[:, 3] = 200.
cmap /= 255.
# Compute t1-images overlays
for name, files in [("aseg", asegfiles), ("wm", wmfiles)]:
for fname in files:
# Get the t1 reference image
subject_id = fname.split("/")[-3]
t1file = t1map[subject_id]
t1_image = nibabel.load(t1file)
# Get the qc output directory
qcdir = os.path.join(os.path.dirname(fname), "qc")
if not os.path.isdir(qcdir):
os.makedirs(qcdir)
# Troncate the color map based on the label max
array = nibabel.load(fname).get_data()
order = sorted(set(array.flatten()))
ccmap = cmap[order[1]:order[-1] + 1]
# Overlay the current image with the t1 image
qcname = "t1-{0}".format(name)
snap_file = os.path.join(qcdir, qcname + ".png")
plot_image(t1file,
overlay_file=fname,
snap_file=snap_file,
name=qcname,
overlay_cmap=ccmap,
cut_coords=(0, 0, 0))
qcfiles.append(snap_file)
return qcfiles
