def get_contour_boundary_points(contour):
"""Get boundary coordinates from contour"""
# First convert the contour image to array
contour_boundary = get_contour_boundary(contour)
contour_boundary_array = sitkh.GetArrayFromImage(contour_boundary)
boundary_index = np.asarray(np.nonzero(contour_boundary_array))
# Convert index to actual coordinates
boundary_points = list()
if len(contour.GetSize()) == 3:
# 3D
for i in range(boundary_index.shape[1]):
boundary_points.append(
contour_boundary.TransformContinuousIndexToPhysicalPoint([
boundary_index[0, i], boundary_index[1, i],
boundary_index[2, i]
]))
else:
# Assume 2D
for i in range(boundary_index.shape[1]):
boundary_points.append(
contour_boundary.TransformContinuousIndexToPhysicalPoint(
[boundary_index[0, i], boundary_index[1, i]]))
boundary_points = np.asarray(boundary_points)
boundary_points = sort_points(boundary_points)
# Add last point to ensure fully connected contour
boundary_points = np.append(boundary_points, boundary_points[0:1], 0)
return boundary_points
def get_masked_slices_mask(mask_image):
'''
Remove the axial slices in a 3-D mask array for which there are non-zero
elements.
Parameters
----------
mask_image: numpy array, mandatory
Boolean 3D array.
Returns
-----------
mask_sliced: numpy array, mandatory
Array containing only those slices of which there are non-zero
elements in the mask.
'''
mask_array = sitkh.GetArrayFromImage(mask_image)
# Filter out slices where there is no mask (need actual index here)
mask_slices = np.flatnonzero(np.any(mask_array, axis=(0, 1)))
if len(mask_slices) == 1:
mask_sliced = mask_image[:, :, mask_slices[0]:(mask_slices[0] + 1)]
else:
mask_sliced = mask_image[:, :, mask_slices[0]:mask_slices[-1]]
return mask_sliced
def get_masked_slices_mask(mask_image):
mask_array = sitkh.GetArrayFromImage(mask_image)
# Filter out slices where there is no mask (need actual index here)
mask_slices = np.flatnonzero(np.any(mask_array, axis=(0, 1)))
mask_sliced = mask_image[:, :, mask_slices[0]:mask_slices[-1]]
return mask_sliced
def get_not_voi_voxels(contour, image):
"""Sets all voxels within VOI to 0"""
contour = sitk.Cast(sitk.Not(contour), image.GetPixelID())
voi_voxels = image * contour
voi_array = sitkh.GetArrayFromImage(voi_voxels)
voi_array_nz = voi_array[np.nonzero(voi_array)]
return voi_array, voi_array_nz
def get_voi_voxels(contour, image):
"""Gives back VOI (non-zero slices), and indices of slices"""
contour = sitk.Cast(contour, image.GetPixelID())
# VOI is only where contour is 1
voi_voxels = image * contour
voi_array = sitkh.GetArrayFromImage(voi_voxels)
voi_array_nz = voi_array[np.nonzero(voi_array)]
new_voi = list()
voi_slices = list()
for i_slice in range(0, voi_array.shape[2]):
if np.count_nonzero(voi_array[:, :, i_slice]) > 0:
new_voi.append(voi_array[:, :, i_slice])
voi_slices.append(i_slice)
new_voi = np.asarray(new_voi)
# Transpose because new_voi was constructed as list of slices, want slice
# index last
new_voi = np.transpose(new_voi, [1, 2, 0])
voi_slices = np.asarray(voi_slices)
return new_voi, voi_array_nz, voi_slices
