anatomical.py 文件源码

def _run_interface(self, runtime):
        in_file = nb.load(self.inputs.in_file)
        data = in_file.get_data()
        mask = np.zeros_like(data, dtype=np.uint8)
        mask[data <= 0] = 1

        # Pad one pixel to control behavior on borders of binary_opening
        mask = np.pad(mask, pad_width=(1,), mode='constant', constant_values=1)

        # Remove noise
        struc = nd.generate_binary_structure(3, 2)
        mask = nd.binary_opening(mask, structure=struc).astype(
            np.uint8)

        # Remove small objects
        label_im, nb_labels = nd.label(mask)
        if nb_labels > 2:
            sizes = nd.sum(mask, label_im, list(range(nb_labels + 1)))
            ordered = list(reversed(sorted(zip(sizes, list(range(nb_labels + 1))))))
            for _, label in ordered[2:]:
                mask[label_im == label] = 0

        # Un-pad
        mask = mask[1:-1, 1:-1, 1:-1]

        # If mask is small, clean-up
        if mask.sum() < 500:
            mask = np.zeros_like(mask, dtype=np.uint8)

        out_img = in_file.__class__(mask, in_file.affine, in_file.header)
        out_img.header.set_data_dtype(np.uint8)

        out_file = fname_presuffix(self.inputs.in_file,
                                   suffix='_rotmask', newpath='.')
        out_img.to_filename(out_file)
        self._results['out_file'] = out_file
        return runtime