b92be51f6fc463ab7deef20fab640b3b2f50b497,doc/examples/brain_extraction.py,,,#,5

Before Change

mask = hist_mask(b0)

nib.save(nib.Nifti1Image(b0, affine), "b0.nii.gz")
nib.save(nib.Nifti1Image(mask.astype("byte"), affine), "mask.nii.gz")

After Change

//img, gtab = read_stanford_hardi()


files = ["./test_bench/Stanford/b0.nii.gz", 
         "./test_bench/3T/GE/b0.nii.gz", 
         "./test_bench/3T/Siemens/b0.nii.gz", 
         "./test_bench/3T/Philips/b0.nii.gz",
         "./test_bench/1.5T/GE/b0.nii.gz", 
         "./test_bench/1.5T/Siemens/b0.nii.gz"]

for f in files:

    img = nib.load(f)

    b0 = img.get_data().squeeze()
    affine = img.get_affine()

    //b0 = np.mean(data[..., 0:9], axis=-1)

    mask = hist_mask(b0)

    //nib.save(nib.Nifti1Image(b0, affine), f + "b0.nii.gz")
    nib.save(nib.Nifti1Image(mask.astype("byte"), affine), f + "_mask.nii.gz")

Instances