def display_unit(self):
"""Adds slice collage, with seg overlays on MRI in each panel."""
if 'cortical' in self.vis_type:
if not self.no_surface_vis and self.current_unit_id in self.surface_vis_paths:
surf_paths = self.surface_vis_paths[
self.current_unit_id] # is a dict of paths
for sf_ax_index, ((hemi, view),
spath) in enumerate(surf_paths.items()):
plt.sca(self.axes[sf_ax_index])
img = mpimg.imread(spath)
# img = crop_image(img)
h_surf = plt.imshow(img)
self.axes[sf_ax_index].text(0, 0,
'{} {}'.format(hemi, view))
self.UI.data_handles.append(h_surf)
else:
msg = 'no surface visualizations\navailable or disabled'
print('{} for {}'.format(msg, self.current_unit_id))
self.axes[1].text(0.5, 0.5, msg)
slices = pick_slices(self.current_seg, self.views,
self.num_slices_per_view)
for vol_ax_index, (dim_index, slice_index) in enumerate(slices):
panel_index = self.volumetric_start_index + vol_ax_index
plt.sca(self.axes[panel_index])
slice_mri = get_axis(self.current_t1_mri, dim_index, slice_index)
slice_seg = get_axis(self.current_seg, dim_index, slice_index)
mri_rgba = self.mri_mapper.to_rgba(slice_mri, alpha=self.alpha_mri)
# self.h_images_mri[ax_index].set_data(mri_rgb)
h_m = plt.imshow(mri_rgba,
interpolation='none',
aspect='equal',
origin='lower')
self.UI.data_handles.append(h_m)
if 'volumetric' in self.vis_type:
seg_rgba = self.seg_mapper.to_rgba(slice_seg,
alpha=self.alpha_seg)
# self.h_images_seg[ax_index].set_data(seg_rgb)
h_seg = plt.imshow(seg_rgba,
interpolation='none',
aspect='equal',
origin='lower')
self.togglable_handles.append(h_seg)
# self.UI.data_handles.append(h_seg)
del seg_rgba
elif 'contour' in self.vis_type:
h_seg = self.plot_contours_in_slice(slice_seg,
self.axes[panel_index])
for contours in h_seg:
self.togglable_handles.extend(contours.collections)
# for clearing upon review
self.UI.data_handles.extend(contours.collections)
del slice_seg, slice_mri, mri_rgba
self.update_histogram()
def mix_and_display(self):
"""Static mix and display."""
# TODO maintain a dict mixed[vis_type] to do computation only once
for ax_index, (dim_index, slice_index) in enumerate(self.slices):
slice_one = get_axis(self.image_one, dim_index, slice_index)
slice_two = get_axis(self.image_two, dim_index, slice_index)
mixed_slice = self.mixer(slice_one, slice_two)
# mixed_slice is already in RGB mode m x p x 3, so
# prev. cmap (gray) has no effect on color_mixed data
self.h_images[ax_index].set_data(mixed_slice)
def attach_image_to_foreground_axes(self, image3d, cmap='gray'):
"""Attaches a given image to the foreground axes and bring it forth"""
image3d = crop_image(image3d, self.padding)
image3d = scale_0to1(image3d)
slices = pick_slices(image3d, self.views, self.num_slices_per_view)
for ax_index, (dim_index, slice_index) in enumerate(slices):
slice_data = get_axis(image3d, dim_index, slice_index)
self.images_fg[ax_index].set(data=slice_data, cmap=cmap)
for ax in self.fg_axes:
ax.set(visible=True, zorder=self.layer_order_zoomedin)
def show_image(self, img, annot=None):
"""Display the requested slices of an image on the existing axes."""
for ax_index, (dim_index, slice_index) in enumerate(self.slices):
self.h_images[ax_index].set_data(
get_axis(img, dim_index, slice_index))
if annot is not None:
self._identify_foreground(annot)
else:
self.fg_annot_h.set_visible(False)
def display_unit(self):
"""Adds slice collage to the given axes"""
# crop and rescale
img = crop_image(self.current_img, self.padding)
img = scale_0to1(img)
# adding slices
slices = pick_slices(img, self.views, self.num_slices_per_view)
for ax_index, (dim_index, slice_index) in enumerate(slices):
slice_data = get_axis(img, dim_index, slice_index)
self.images[ax_index].set_data(slice_data)
# updating histogram
self.update_histogram(img)
def overlay_images(qcw, mri, seg,
subject_id=None,
annot=None,
figsize=None,
padding=default_padding,
output_path=None):
"""Backend engine for overlaying a given seg on MRI with freesurfer label."""
num_rows_per_view, num_slices_per_view, padding = check_params(qcw.num_rows, qcw.num_slices, padding)
mri, seg = crop_to_seg_extents(mri, seg, padding)
surf_vis = dict() # empty - no vis to include
# TODO broaden this to include subcortical structures as well
if 'cortical' in qcw.vis_type:
if qcw.in_dir is not None and subject_id is not None and qcw.out_dir is not None:
surf_vis = make_vis_pial_surface(qcw.in_dir, subject_id, qcw.out_dir)
num_surf_vis = len(surf_vis)
# TODO calculation below is redundant, if surf vis does not fail
# i.e. if num_surf_vis is fixed, no need to recompute for every subject
num_views = len(qcw.views)
num_rows = num_rows_per_view * num_views
slices = pick_slices(seg, qcw.views, num_slices_per_view)
num_volumetric_slices = len(slices)
total_num_panels = num_volumetric_slices + num_surf_vis
num_rows_for_surf_vis = 1 if num_surf_vis > 0 else 0
num_rows = num_rows + num_rows_for_surf_vis
num_cols = check_layout(total_num_panels, num_views, num_rows_per_view, num_rows_for_surf_vis)
plt.style.use('dark_background')
if figsize is None:
# figsize = [min(15,4*num_rows), min(12,4*num_cols)] # max (15,12)
figsize = [4 * num_rows, 2* num_cols]
fig, ax = plt.subplots(num_rows, num_cols, figsize=figsize)
display_params_mri = dict(interpolation='none', aspect='equal', origin='lower',
alpha=qcw.alpha_mri)
display_params_seg = dict(interpolation='none', aspect='equal', origin='lower',
alpha=qcw.alpha_seg)
normalize_labels = colors.Normalize(vmin=seg.min(), vmax=seg.max(), clip=True)
fs_cmap = get_freesurfer_cmap(qcw.vis_type)
seg_mapper = cm.ScalarMappable(norm=normalize_labels, cmap=fs_cmap)
normalize_mri = colors.Normalize(vmin=mri.min(), vmax=mri.max(), clip=True)
mri_mapper = cm.ScalarMappable(norm=normalize_mri, cmap='gray')
# deciding colors for the whole image
unique_labels = np.unique(seg)
# removing background - 0 stays 0
unique_labels = np.delete(unique_labels, 0)
if len(unique_labels) == 1:
color4label = [qcw.contour_color]
else:
color4label = seg_mapper.to_rgba(unique_labels)
handles_seg = list()
handles_mri = list()
ax = ax.flatten()
# display surfaces
for sf_counter, ((hemi, view), spath) in enumerate(surf_vis.items()):
plt.sca(ax[sf_counter])
img = mpimg.imread(spath)
# img = crop_image(img)
plt.imshow(img)
ax[sf_counter].text(0, 0, '{} {}'.format(hemi, view))
plt.axis('off')
# display slices
for ax_counter, (dim_index, slice_num) in enumerate(slices):
plt.sca(ax[ax_counter + num_surf_vis])
slice_mri = get_axis(mri, dim_index, slice_num)
slice_seg = get_axis(seg, dim_index, slice_num)
# display MRI
mri_rgb = mri_mapper.to_rgba(slice_mri)
h_mri = plt.imshow(mri_rgb, **display_params_mri)
if 'volumetric' in qcw.vis_type:
seg_rgb = seg_mapper.to_rgba(slice_seg)
h_seg = plt.imshow(seg_rgb, **display_params_seg)
elif 'contour' in qcw.vis_type:
h_seg = plot_contours_in_slice(slice_seg, unique_labels, color4label)
plt.axis('off')
# # encoding the souce of the object (image/line) being displayed
# handle_seg.set_label('seg {} {}'.format(dim_index, slice_num))
# handle_mri.set_label('mri {} {}'.format(dim_index, slice_num))
handles_mri.append(h_mri)
if len(h_seg) >= 1:
handles_seg.extend(h_seg)
else:
handles_seg.append(h_seg)
# hiding unused axes
for ua in range(total_num_panels, len(ax)):
ax[ua].set_visible(False)
if annot is not None:
h_annot = fig.suptitle(annot, **cfg.annot_text_props)
h_annot.set_position(cfg.position_annot_text)
fig.set_size_inches(figsize)
if output_path is not None:
# no space left unused
plt.subplots_adjust(**cfg.no_blank_area)
output_path = output_path.replace(' ', '_')
layout_str = 'v{}_ns{}_{}x{}'.format(''.join([ str(v) for v in qcw.views]),num_slices_per_view,num_rows,num_cols)
fig.savefig(output_path + '_{}.png'.format(layout_str), bbox_inches='tight')
# leaving some space on the right for review elements
plt.subplots_adjust(**cfg.review_area)
return fig, handles_mri, handles_seg, figsize