def draw_segs_on_slice(vol_slice,
seg_slice,
include_labels=None,
colors=None,
draw_contours=False,
use_gradient_colormap=False):
'''
Overlays segmentations on a 2D slice.
:param vol_slice: h x w image, the brain slice to overlay on top of
:param seg_slice: h x w array, segmentations to overlay
(in labels format, not one hot)
:param include_labels: list, visualize only specific label values
:param colors: n_labels x 3, specific colors to use for segmentations
:param draw_contours: bool, visualize segmentations as contours
rather than solid areas
:param use_gradient_colormap: bool, create the colormap as a gradient of a
single color rather than a rainbow
:return: h x w x 3 image of brain slice with segmentations overlaid on top
'''
# if no labels are specified, simply visualize all unique label values
if include_labels is None:
include_labels = list(np.unique(seg_slice).astype(int))
# if colors are not specified, make a color map
if colors is None:
if use_gradient_colormap:
colors = make_cmap_gradient(len(include_labels) + 1, hue=0.5)
else:
colors = make_cmap_rainbow(len(include_labels) + 1)
# make a new segmentation map with labels as ascending integers,
# since this is what segutils expects
pruned_slice = np.zeros(seg_slice.shape, dtype=int)
for i, l in enumerate(include_labels):
pruned_slice[seg_slice == l] = i + 1
seg_im = pynd_segutils.seg_overlap(np.squeeze(vol_slice),
pruned_slice,
cmap=colors,
do_contour=draw_contours)
return seg_im
def visualize_seg_contour(vol,
seg,
region_numbers=[4],
slice_idx=[80, 90, 110],
title=''):
if title != '':
title += ', '
normalized_vol = vol / np.max(vol)
seg_one_region = np.zeros(seg.shape)
for num in region_numbers:
seg_one_region[seg == num] = num
img = seg_overlap(normalized_vol, seg_one_region.astype(np.int))
plt.figure(figsize=(20, 10))
slices([
img[slice_idx[0], :, :, :], img[:, slice_idx[1], :, :],
img[:, :, slice_idx[2], :]
],
titles=[
title + 'x=%d' % slice_idx[0], title + 'y=%d' % slice_idx[1],
title + 'z=%d' % slice_idx[2]
])