Source code for ants.utils.mask_image

__all__ = ['mask_image']

import numpy as np
from .threshold_image import threshold_image


[docs]def mask_image(image, mask, level=1, binarize=False): """ Mask an input image by a mask image. If the mask image has multiple labels, it is possible to specify which label(s) to mask at. ANTsR function: `maskImage` Arguments --------- image : ANTsImage Input image. mask : ANTsImage Mask or label image. level : scalar or tuple of scalars Level(s) at which to mask image. If vector or list of values, output image is non-zero at all locations where label image matches any of the levels specified. binarize : boolean whether binarize the output image Returns ------- ANTsImage Example ------- >>> import ants >>> myimage = ants.image_read(ants.get_ants_data('r16')) >>> mask = ants.get_mask(myimage) >>> myimage_mask = ants.mask_image(myimage, mask, 3) >>> seg = ants.kmeans_segmentation(myimage, 3) >>> myimage_mask = ants.mask_image(myimage, seg['segmentation'], (1,3)) """ leveluse = level if type(leveluse) is np.ndarray: leveluse = level.tolist() if type(leveluse) is int or type(leveluse) is float: leveluse = [level] image_out = image.clone() * 0 for mylevel in leveluse: temp = threshold_image(mask, mylevel, mylevel) if binarize: image_out = image_out + temp else: image_out = image_out + temp * image return image_out