scipy.ndimage

问题 I am trying to analyze greyscale TIFF stacks, in which a given frame will look like this. I filter it (using Gaussian blur), and then binarize it (using Otsu's method for threshold). MATLAB code, which works great: image_conncomp = bwconncomp(image_binary); # entire stack is held in image_binary for i=1:image_conncomp.NumObjects object_size = length(image_conncomp.PixelIdxList{i}); end Each white spot in the example image is picked up, and its volume (in pixels) is pretty accurately given by

问题 I am trying to analyze greyscale TIFF stacks, in which a given frame will look like this. I filter it (using Gaussian blur), and then binarize it (using Otsu's method for threshold). MATLAB code, which works great: image_conncomp = bwconncomp(image_binary); # entire stack is held in image_binary for i=1:image_conncomp.NumObjects object_size = length(image_conncomp.PixelIdxList{i}); end Each white spot in the example image is picked up, and its volume (in pixels) is pretty accurately given by

问题 I want to resize(downscale) the ground truth 3d images of brain tumor segmentation. Here are some g.t. + brain images: G.t. images are 3d numpy array and consist of only 0 and 1 value(only green voxel and black voxel, brain is not included in g.t. image). def resize(img, shape, mode='nearest', orig_shape=None, order=3): """ Wrapper for scipy.ndimage.zoom suited for MRI images. """ if orig_shape == None: orig_shape = img.shape assert len(shape) == 3, "Can not have more than 3 dimensions"