def volume_images(data_dir, subj):
"""Plot a mosiac of the brainmask and aseg volumes."""
# Plot the volume slices
brain_file = op.join(data_dir, subj, "mri/brainmask.mgz")
# Load the cortical ribbon file and use same index for both hemis
ribbon_file = op.join(data_dir, subj, "mri/ribbon.mgz")
ribbon_data = nib.load(ribbon_file).get_data().astype(float)
ribbon_data[ribbon_data == 3] = 1
ribbon_data[ribbon_data == 42] = 1
ribbon_data[ribbon_data != 1] = np.nan
# Load the aseg file and use it to derive a FOV mask
aseg_file = op.join(data_dir, subj, "mri/aseg.mgz")
aseg_data = nib.load(aseg_file).get_data()
aseg_data[aseg_data == 41] = 2
mask_data = (aseg_data > 0).astype(int)
# Load the lookup table for the aseg volume
aseg_lut = np.genfromtxt(
op.join(os.environ["FREESURFER_HOME"], "FreeSurferColorLUT.txt"))
# Draw the brainmask and cortical ribbon
m = Mosaic(brain_file, ribbon_data, mask_data, step=3)
m.plot_mask("#C41E3A")
m.savefig(op.join(data_dir, subj, "snapshots/volume.png"))
m.close()
# Draw the brainmask and cortical ribbon
aseg_cmap = mpl.colors.ListedColormap(aseg_lut[:64, 2:5] / 255)
m = Mosaic(brain_file, aseg_data, mask_data, step=3)
m.plot_overlay(aseg_cmap, vmin=0, vmax=63, alpha=.75, colorbar=False)
m.savefig(op.join(data_dir, subj, "snapshots/aseg.png"))
m.close()
def volume_images(data_dir, subj):
"""Plot a mosiac of the brainmask and aseg volumes."""
# Plot the volume slices
brain_file = op.join(data_dir, subj, "mri/brainmask.mgz")
# Load the cortical ribbon file and use same index for both hemis
ribbon_file = op.join(data_dir, subj, "mri/ribbon.mgz")
ribbon_data = nib.load(ribbon_file).get_data().astype(float)
ribbon_data[ribbon_data == 3] = 1
ribbon_data[ribbon_data == 42] = 1
ribbon_data[ribbon_data != 1] = np.nan
# Load the aseg file and use it to derive a FOV mask
aseg_file = op.join(data_dir, subj, "mri/aseg.mgz")
aseg_data = nib.load(aseg_file).get_data()
aseg_data[aseg_data == 41] = 2
mask_data = (aseg_data > 0).astype(int)
# Load the lookup table for the aseg volume
aseg_lut = np.genfromtxt(op.join(os.environ["FREESURFER_HOME"],
"FreeSurferColorLUT.txt"))
# Draw the brainmask and cortical ribbon
m = Mosaic(brain_file, ribbon_data, mask_data, step=3)
m.plot_mask("#C41E3A")
m.savefig(op.join(data_dir, subj, "snapshots/volume.png"))
m.close()
# Draw the brainmask and cortical ribbon
aseg_cmap = mpl.colors.ListedColormap(aseg_lut[:64, 2:5] / 255)
m = Mosaic(brain_file, aseg_data, mask_data, step=3)
m.plot_overlay(aseg_cmap, vmin=0, vmax=63, alpha=.75, colorbar=False)
m.savefig(op.join(data_dir, subj, "snapshots/aseg.png"))
m.close()
def plot_mask_image(self):
m = Mosaic(self.inputs.orig_file, self.inputs.mask_file,
self.inputs.mask_file, show_mask=False, step=1)
m.plot_mask()
m.savefig("functional_mask.png")
m.close()
def plot_mask(self):
"""Plot the analysis mask."""
m = Mosaic(stat=self.inputs.mask_file)
m.plot_mask()
out_fname = nii_to_png(self.inputs.mask_file)
self.out_files.append(out_fname)
m.savefig(out_fname)
m.close()
def plot_mask(self):
"""Plot the analysis mask."""
m = Mosaic(stat=self.inputs.mask_file)
m.plot_mask()
out_fname = nii_to_png(self.inputs.mask_file)
self.out_files.append(out_fname)
m.savefig(out_fname)
m.close()
def plot_mask_image(self):
m = Mosaic(self.inputs.orig_file,
self.inputs.mask_file,
self.inputs.mask_file,
show_mask=False,
step=1)
m.plot_mask()
m.savefig("functional_mask.png")
m.close()
