64faf99202c30fedc666f9846f8af017cecf8efd,nilearn/masking.py,,compute_gray_matter_mask,#,522

Before Change

    from .datasets import load_mni152_brain_mask
    template = load_mni152_brain_mask()
    dtype = img_data_dtype(target_img)
    template = new_img_like(template,
                            get_data(template).astype(dtype))

    from .image.resampling import resample_to_img
    resampled_template = cache(resample_to_img, memory)(template, target_img)

    mask = get_data(resampled_template) >= threshold

    mask, affine = _post_process_mask(mask, target_img.affine, opening=opening,
                                      connected=connected,
                                      warning_msg="Gray matter mask is empty, "
                                                  "lower the threshold or "
                                                  "check your input FOV")

    return new_img_like(target_img, mask, affine)


def compute_multi_gray_matter_mask(target_imgs, threshold=.5,
                                   connected=True, opening=2,

After Change

    mask : nibabel.Nifti1Image
        The brain mask (3D image)
    
    return compute_brain_mask(target_img=target_img, threshold=threshold,
                              connected=connected, opening=opening,
                              memory=memory, verbose=verbose)


def compute_brain_mask(target_img, threshold=.5, connected=True,
                       opening=2, memory=None, verbose=0):

Instances