def compute_nifti_bounding_box(img):
"""Finds bounding box from data and transforms it in world space for use
on data with different attributes like voxel size."""
data = img.get_fdata(dtype=np.float32, caching='unchanged')
affine = img.affine
voxel_size = img.header.get_zooms()[0:3]
voxel_bb_mins, voxel_bb_maxs = bounding_box(data)
world_bb_mins = voxel_to_world(voxel_bb_mins, affine)
world_bb_maxs = voxel_to_world(voxel_bb_maxs, affine)
wbbox = WorldBoundingBox(world_bb_mins, world_bb_maxs, voxel_size)
return wbbox
def crop_nifti(img, wbbox):
"""Applies cropping from a world space defined bounding box and fixes the
affine to keep data aligned."""
data = img.get_fdata(dtype=np.float32, caching='unchanged')
affine = img.affine
voxel_bb_mins = world_to_voxel(wbbox.minimums, affine)
voxel_bb_maxs = world_to_voxel(wbbox.maximums, affine)
# Prevent from trying to crop outside data boundaries by clipping bbox
extent = list(data.shape[:3])
for i in range(3):
voxel_bb_mins[i] = max(0, voxel_bb_mins[i])
voxel_bb_maxs[i] = min(extent[i], voxel_bb_maxs[i])
translation = voxel_to_world(voxel_bb_mins, affine)
data_crop = np.copy(crop(data, voxel_bb_mins, voxel_bb_maxs))
new_affine = np.copy(affine)
new_affine[0:3, 3] = translation[0:3]
return nib.Nifti1Image(data_crop, new_affine)