def surf_convert(fsdir, t1files, surffiles, output_directory=None,
rm_orig=False,
fsconfig="/i2bm/local/freesurfer/SetUpFreeSurfer.sh"):
""" Export FreeSurfer surfaces to the native space.
Note that all the vetices are given in the index coordinate system.
The subjecy id in the t1 and surf files must appear in the -3 position:
xxx/subject_id/convert/t1.nii.gz
<unit>
<input name="fsdir" type="Directory" description="The
freesurfer working directory with all the subjects."/>
<input name="output_directory" type="Directory" description="The
conversion destination folder."/>
<input name="t1files" type="List_File" description="The t1 nifti
files."/>
<input name="surffiles" type="List_File" description="The surface
to be converted."/>
<input name="rm_orig" type="Bool" description="If true remove
the input surfaces."/>
<input name="fsconfig" type="File" description="The freesurfer
configuration batch."/>
<output name="csurffiles" type="List_File" description="The converted
surfaces in the native space."/>
</unit>
"""
# Create a t1 subject map
t1map = {}
for fname in t1files:
subject_id = fname.split("/")[-3]
if subject_id in t1map:
raise ("Can't map two t1 for subject '{0}'.".format(subject_id))
t1map[subject_id] = fname
# Convert all the surfaces
csurffiles = []
for fname in surffiles:
# Get the t1 reference image
subject_id = fname.split("/")[-3]
t1file = t1map[subject_id]
t1_image = nibabel.load(t1file)
# Compute the conformed space to the native anatomical deformation
asegfile = os.path.join(fsdir, subject_id, "mri", "aseg.mgz")
physical_to_index = numpy.linalg.inv(t1_image.get_affine())
translation = tkregister_translation(asegfile, fsconfig)
deformation = numpy.dot(physical_to_index, translation)
# Load and warp the mesh
# The mesh: a 2-uplet with vertex (x, y, z) coordinates and
# mesh triangles
mesh = freesurfer.read_geometry(fname)
surf = TriSurface(vertices=apply_affine_on_mesh(mesh[0], deformation),
triangles=mesh[1])
# Save the mesh in the native space
outputfile = fname + ".native"
surf.save(os.path.dirname(outputfile), os.path.basename(outputfile))
csurffiles.append(outputfile)
# Clean input surface if specified
if rm_orig:
os.remove(fname)
return csurffiles
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
def qc_profile(nodif_file,
proba_file,
proba_texture,
ico_order,
fsdir,
sid,
outdir,
fsconfig,
actor_ang=(0., 0., 0.)):
""" Connectivity profile QC.
Generates views of:
- the superposition of the nodif image with tractography result volume.
- the connected points on the cortical surface
Resample cortical meshes if needed.
Results output are available as gif and png.
Parameters
----------
nodif_file: str (mandatory)
file for probtrackx2 containing the no diffusion volume and associated
space information.
proba_file: str (mandatory)
the protrackx2 output seeding probabilistic path volume.
proba_texture: dict (mandatory)
the FreeSurfer mri_vol2surf '.mgz' 'lh' and 'rh' textrue that contains
the cortiacal connection strength.
ico_order: int (mandatory)
icosahedron order in [0, 7] that will be used to generate the cortical
surface texture at a specific tessalation (the corresponding cortical
surface can be resampled using the
'clindmri.segmentation.freesurfer.resample_cortical_surface' function).
fsdir: str (mandatory)
FreeSurfer subjects directory 'SUBJECTS_DIR'.
sid: str (mandatory)
FreeSurfer subject identifier.
outdir: str (mandatory)
The QC output directory.
fsconfig: str (mandatory)
the FreeSurfer '.sh' config file.
actor_ang: 3-uplet (optinal, default (0, 0, 0))
the actor x, y, z position (in degrees).
Returns
-------
snaps: list of str
two gifs images, one showing the connection profile as a texture on
the cortical surface, the other a volumic representation of the
deterministic tractography.
"""
import clindmri.plot.pvtk as pvtk
from clindmri.plot.slicer import animate_image
# Construct/check the subject directory
subjectdir = os.path.join(fsdir, sid)
if not os.path.isdir(subjectdir):
raise ValueError(
"'{0}' is not a FreeSurfer subject directory.".format(subjectdir))
# Check that the output QC directory exists
if not os.path.isdir(outdir):
os.makedirs(outdir)
# Superpose the nodif and probabilistic tractography volumes
proba_shape = nibabel.load(proba_file).shape
snaps = []
snaps.append(
animate_image(nodif_file,
overlay_file=proba_file,
clean=True,
overlay_cmap="Spectral",
cut_coords=proba_shape[2],
outdir=outdir))
# Define a renderer
ren = pvtk.ren()
# For each hemisphere
for hemi in ["lh", "rh"]:
# Get the the white mesh on the desired icosphere
meshfile = os.path.join(subjectdir, "convert",
"{0}.white.{1}.native".format(hemi, ico_order))
if not os.path.isfile(meshfile):
raise ValueError(
"'{0}' is not a valid white mesh. Generate it through the "
"'clindmri.scripts.freesurfer_conversion' script.".format(
meshfile))
# Check texture has the expected extension, size
texture_file = proba_texture[hemi]
if not texture_file.endswith(".mgz"):
raise ValueError("'{0}' is not a '.mgz' file. Format not "
"supported.".format(texture_file))
profile_array = nibabel.load(texture_file).get_data()
profile_dim = profile_array.ndim
profile_shape = profile_array.shape
if profile_dim != 3:
raise ValueError(
"Expected profile texture array of dimension 3 not "
"'{0}'".format(profile_dim))
if (profile_shape[1] != 1) or (profile_shape[2] != 1):
raise ValueError(
"Expected profile texture array of shape (*, 1, 1) not "
"'{0}'.".format(profile_shape))
# Flatten the profile texture array
texture = profile_array.ravel()
# Load the white mesh
surface = TriSurface.load(meshfile)
# Define a textured surface actor
actor = pvtk.surface(surface.vertices, surface.triangles, texture)
actor.RotateX(actor_ang[0])
actor.RotateY(actor_ang[1])
actor.RotateZ(actor_ang[2])
pvtk.add(ren, actor)
# Create a animaton with the generated surface
qcname = "profile_as_texture"
snaps.extend(
pvtk.record(ren,
outdir,
qcname,
n_frames=36,
az_ang=10,
animate=True,
delay=10))
return snaps
mesharray = numpy.zeros(t1shape, dtype=numpy.uint)
for basename in surf:
# > construc path
fpath = os.path.join(mripath, basename)
if not os.path.isfile(fpath):
raise ValueError("'{0}' is not a valid file name.".format(fpath))
surf[basename] = fpath
# > load mesh
name = basename.split(".")[1]
annot_basename = basename.replace(
name, "aparc.annot").replace(".native", "")
annotfile = os.path.join(mripath, annot_basename)
if not os.path.isfile(fpath):
raise ValueError("'{0}' is not a valid file name.".format(fpath))
surface = TriSurface.load(fpath, annotfile=annotfile)
# > binarize mesh
indices = numpy.round(surface.vertices).astype(int).T
indices[0, numpy.where(indices[0] >= t1shape[0])] = 0
indices[1, numpy.where(indices[1] >= t1shape[1])] = 0
indices[2, numpy.where(indices[2] >= t1shape[2])] = 0
mesharray[indices.tolist()] = colors[basename]
# Save the mesh volume
meshim = nibabel.Nifti1Image(mesharray, t1affine)
nibabel.save(meshim, meshfile)
# Need to reorient the image to MNI standard space
reomeshfile = os.path.join(qcdir, "reo." + os.path.basename(meshfile))
fslreorient2std(meshfile, reomeshfile, shfile=fslconfig)
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
def display_folds(folds_file,
labels,
weights,
white_file=None,
interactive=True,
snap=False,
animate=False,
outdir=None,
name="folds",
actor_ang=(0., 0., 0.)):
""" Display the folds computed by morphologist.
The scene supports one feature activated via the keystroke:
* 'p': Pick the data at the current mouse point. This will pop-up a window
with information on the current pick (ie. the fold name).
Parameters
----------
folds_file: str( mandatory)
the folds '.gii' file.
labels: dict (mandatory)
a mapping between a mesh id and its label.
weights: dict (mandatory)
a mapping between a mesh label and its wheight in [0, 1].
white_file: str (optional, default None)
if specified the white surface will be displayed.
interactive: bool (optional, default True)
if True display the renderer.
snap: bool (optional, default False)
if True create a snap of the scene: need a valid outdir.
animate: bool (optional, default False)
if True create a gif 360 degrees animation of the scene: need a valid
outdir.
outdir: str (optional, default None)
an existing directory.
name: str (optional, default 'folds')
the basename of the generated files.
actor_ang: 3-uplet (optinal, default (0, 0, 0))
the actors x, y, z position (in degrees).
"""
# Load the folds file
image = gio.read(folds_file)
nb_of_surfs = len(image.darrays)
if nb_of_surfs % 2 != 0:
raise ValueError("Need an odd number of arrays (vertices, triangles).")
# Create an actor for each fold
ren = pvtk.ren()
ren.SetBackground(1, 1, 1)
for vertindex in range(0, nb_of_surfs, 2):
vectices = image.darrays[vertindex].data
triangles = image.darrays[vertindex + 1].data
labelindex = image.darrays[vertindex].get_metadata()["Timestep"]
if labelindex != image.darrays[vertindex +
1].get_metadata()["Timestep"]:
raise ValueError("Gifti arrays '{0}' and '{1}' do not share the "
"same label.".format(vertindex, vertindex + 1))
labelindex = int(labelindex)
if labelindex in labels:
label = labels[labelindex]
if label in weights:
weight = weights[label] * 256.
else:
weight = 0
else:
label = "NC"
weight = 0
surf = TriSurface(vectices, triangles, labels=None)
actor = pvtk.surface(surf.vertices, surf.triangles,
surf.labels + weight)
actor.label = label
actor.RotateX(actor_ang[0])
actor.RotateY(actor_ang[1])
actor.RotateZ(actor_ang[2])
pvtk.add(ren, actor)
# Add the white surface if specified
if white_file is not None:
image = gio.read(white_file)
nb_of_surfs = len(image.darrays)
if nb_of_surfs != 2:
raise ValueError("'{0}' does not a contain a valid white "
"mesh.".format(white_file))
vectices = image.darrays[0].data
triangles = image.darrays[1].data
surf = TriSurface(vectices, triangles, labels=None)
actor = pvtk.surface(surf.vertices,
surf.triangles,
surf.labels,
opacity=1,
set_lut=False)
actor.label = "white"
actor.RotateX(actor_ang[0])
actor.RotateY(actor_ang[1])
actor.RotateZ(actor_ang[2])
pvtk.add(ren, actor)
# Show the renderer
if interactive:
actor = pvtk.text("!!!!",
font_size=15,
position=(10, 10),
is_visible=False)
pvtk.add(ren, actor)
obs = LabelsOnPick(actor,
static_position=True,
to_keep_actors=["white"])
pvtk.show(ren, title="morphologist folds", observers=[obs])
# Create a snap
if snap:
if not os.path.isdir(outdir):
raise ValueError("'{0}' is not a valid directory.".format(outdir))
pvtk.record(ren, outdir, name, n_frames=1)
# Create an animation
if animate:
if not os.path.isdir(outdir):
raise ValueError("'{0}' is not a valid directory.".format(outdir))
pvtk.record(ren,
outdir,
name,
n_frames=36,
az_ang=10,
animate=True,
delay=25)
def surf_convert(fsdir,
t1files,
surffiles,
output_directory=None,
rm_orig=False,
fsconfig="/i2bm/local/freesurfer/SetUpFreeSurfer.sh"):
""" Export FreeSurfer surfaces to the native space.
Note that all the vetices are given in the index coordinate system.
The subjecy id in the t1 and surf files must appear in the -3 position:
xxx/subject_id/convert/t1.nii.gz
<unit>
<input name="fsdir" type="Directory" description="The
freesurfer working directory with all the subjects."/>
<input name="output_directory" type="Directory" description="The
conversion destination folder."/>
<input name="t1files" type="List_File" description="The t1 nifti
files."/>
<input name="surffiles" type="List_File" description="The surface
to be converted."/>
<input name="rm_orig" type="Bool" description="If true remove
the input surfaces."/>
<input name="fsconfig" type="File" description="The freesurfer
configuration batch."/>
<output name="csurffiles" type="List_File" description="The converted
surfaces in the native space."/>
</unit>
"""
# Create a t1 subject map
t1map = {}
for fname in t1files:
subject_id = fname.split("/")[-3]
if subject_id in t1map:
raise ("Can't map two t1 for subject '{0}'.".format(subject_id))
t1map[subject_id] = fname
# Convert all the surfaces
csurffiles = []
for fname in surffiles:
# Get the t1 reference image
subject_id = fname.split("/")[-3]
t1file = t1map[subject_id]
t1_image = nibabel.load(t1file)
# Compute the conformed space to the native anatomical deformation
asegfile = os.path.join(fsdir, subject_id, "mri", "aseg.mgz")
physical_to_index = numpy.linalg.inv(t1_image.get_affine())
translation = tkregister_translation(asegfile, fsconfig)
deformation = numpy.dot(physical_to_index, translation)
# Load and warp the mesh
# The mesh: a 2-uplet with vertex (x, y, z) coordinates and
# mesh triangles
mesh = freesurfer.read_geometry(fname)
surf = TriSurface(vertices=apply_affine_on_mesh(mesh[0], deformation),
triangles=mesh[1])
# Save the mesh in the native space
outputfile = fname + ".native"
surf.save(os.path.dirname(outputfile), os.path.basename(outputfile))
csurffiles.append(outputfile)
# Clean input surface if specified
if rm_orig:
os.remove(fname)
return csurffiles
def qc_profile(nodif_file, proba_file, proba_texture, ico_order,
fsdir, sid, outdir, fsconfig, actor_ang=(0., 0., 0.)):
""" Connectivity profile QC.
Generates views of:
- the superposition of the nodif image with tractography result volume.
- the connected points on the cortical surface
Resample cortical meshes if needed.
Results output are available as gif and png.
Parameters
----------
nodif_file: str (mandatory)
file for probtrackx2 containing the no diffusion volume and associated
space information.
proba_file: str (mandatory)
the protrackx2 output seeding probabilistic path volume.
proba_texture: dict (mandatory)
the FreeSurfer mri_vol2surf '.mgz' 'lh' and 'rh' textrue that contains
the cortiacal connection strength.
ico_order: int (mandatory)
icosahedron order in [0, 7] that will be used to generate the cortical
surface texture at a specific tessalation (the corresponding cortical
surface can be resampled using the
'clindmri.segmentation.freesurfer.resample_cortical_surface' function).
fsdir: str (mandatory)
FreeSurfer subjects directory 'SUBJECTS_DIR'.
sid: str (mandatory)
FreeSurfer subject identifier.
outdir: str (mandatory)
The QC output directory.
fsconfig: str (mandatory)
the FreeSurfer '.sh' config file.
actor_ang: 3-uplet (optinal, default (0, 0, 0))
the actor x, y, z position (in degrees).
Returns
-------
snaps: list of str
two gifs images, one showing the connection profile as a texture on
the cortical surface, the other a volumic representation of the
deterministic tractography.
"""
import clindmri.plot.pvtk as pvtk
from clindmri.plot.slicer import animate_image
# Construct/check the subject directory
subjectdir = os.path.join(fsdir, sid)
if not os.path.isdir(subjectdir):
raise ValueError(
"'{0}' is not a FreeSurfer subject directory.".format(subjectdir))
# Check that the output QC directory exists
if not os.path.isdir(outdir):
os.makedirs(outdir)
# Superpose the nodif and probabilistic tractography volumes
proba_shape = nibabel.load(proba_file).shape
snaps = []
snaps.append(
animate_image(nodif_file, overlay_file=proba_file, clean=True,
overlay_cmap="Spectral", cut_coords=proba_shape[2],
outdir=outdir))
# Define a renderer
ren = pvtk.ren()
# For each hemisphere
for hemi in ["lh", "rh"]:
# Get the the white mesh on the desired icosphere
meshfile = os.path.join(
subjectdir, "convert", "{0}.white.{1}.native".format(
hemi, ico_order))
if not os.path.isfile(meshfile):
raise ValueError(
"'{0}' is not a valid white mesh. Generate it through the "
"'clindmri.scripts.freesurfer_conversion' script.".format(
meshfile))
# Check texture has the expected extension, size
texture_file = proba_texture[hemi]
if not texture_file.endswith(".mgz"):
raise ValueError("'{0}' is not a '.mgz' file. Format not "
"supported.".format(texture_file))
profile_array = nibabel.load(texture_file).get_data()
profile_dim = profile_array.ndim
profile_shape = profile_array.shape
if profile_dim != 3:
raise ValueError(
"Expected profile texture array of dimension 3 not "
"'{0}'".format(profile_dim))
if (profile_shape[1] != 1) or (profile_shape[2] != 1):
raise ValueError(
"Expected profile texture array of shape (*, 1, 1) not "
"'{0}'.".format(profile_shape))
# Flatten the profile texture array
texture = profile_array.ravel()
# Load the white mesh
surface = TriSurface.load(meshfile)
# Define a textured surface actor
actor = pvtk.surface(surface.vertices, surface.triangles, texture)
actor.RotateX(actor_ang[0])
actor.RotateY(actor_ang[1])
actor.RotateZ(actor_ang[2])
pvtk.add(ren, actor)
# Create a animaton with the generated surface
qcname = "profile_as_texture"
snaps.extend(
pvtk.record(ren, outdir, qcname, n_frames=36, az_ang=10, animate=True,
delay=10))
return snaps
if trf_file is None:
trf_file = os.path.join(connectdir, "dmri_to_t1.trf")
reg_file = os.path.join(connectdir, "nodif_to_t1.nii.gz")
flirt(nodif_file,
t1_file,
omat=trf_file,
out=reg_file,
usesqform=False,
cost="normmi",
dof=6)
"""
Launch the tractography on the requested point of the cortical surface on the
selected hemisphere
"""
# Load the white mesh in the diffusion space
surface = TriSurface.load(whitefile)
voxel_diff_to_t1 = flirt2aff(trf_file, nodif_file, t1_file)
voxel_t1_to_diff = numpy.linalg.inv(voxel_diff_to_t1)
white_diff_vertices = apply_affine_on_mesh(surface.vertices, voxel_t1_to_diff)
# Select the vertices of interest
if vertices_indices is None:
vertices_indices = range(len(surface.vertices))
# Go through all the hemisphere vertices
textures = {}
for index in vertices_indices:
# Select the seeding vertex
point = white_diff_vertices[index]
mesharray = numpy.zeros(t1shape, dtype=numpy.uint)
for basename in surf:
# > construc path
fpath = os.path.join(mripath, basename)
if not os.path.isfile(fpath):
raise ValueError("'{0}' is not a valid file name.".format(fpath))
surf[basename] = fpath
# > load mesh
name = basename.split(".")[1]
annot_basename = basename.replace(name,
"aparc.annot").replace(".native", "")
annotfile = os.path.join(mripath, annot_basename)
if not os.path.isfile(fpath):
raise ValueError("'{0}' is not a valid file name.".format(fpath))
surface = TriSurface.load(fpath, annotfile=annotfile)
# > binarize mesh
indices = numpy.round(surface.vertices).astype(int).T
indices[0, numpy.where(indices[0] >= t1shape[0])] = 0
indices[1, numpy.where(indices[1] >= t1shape[1])] = 0
indices[2, numpy.where(indices[2] >= t1shape[2])] = 0
mesharray[indices.tolist()] = colors[basename]
# Save the mesh volume
meshim = nibabel.Nifti1Image(mesharray, t1affine)
nibabel.save(meshim, meshfile)
# Need to reorient the image to MNI standard space
reomeshfile = os.path.join(qcdir, "reo." + os.path.basename(meshfile))
fslreorient2std(meshfile, reomeshfile, shfile=fslconfig)
If no '.trf' file is provided, register the nodif image on the t1 image
to get it.
"""
if trf_file is None:
trf_file = os.path.join(connectdir, "dmri_to_t1.trf")
reg_file = os.path.join(connectdir, "nodif_to_t1.nii.gz")
flirt(nodif_file, t1_file, omat=trf_file, out=reg_file, usesqform=False,
cost="normmi", dof=6)
"""
Launch the tractography on the requested point of the cortical surface on the
selected hemisphere
"""
# Load the white mesh in the diffusion space
surface = TriSurface.load(whitefile)
voxel_diff_to_t1 = flirt2aff(trf_file, nodif_file, t1_file)
voxel_t1_to_diff = numpy.linalg.inv(voxel_diff_to_t1)
white_diff_vertices = apply_affine_on_mesh(surface.vertices, voxel_t1_to_diff)
# Select the vertices of interest
if vertices_indices is None:
vertices_indices = range(len(surface.vertices))
# Go through all the hemisphere vertices
textures = {}
for index in vertices_indices:
# Select the seeding vertex
point = white_diff_vertices[index]