f5665c4258e60c7e93b3cac79bebefd5906af6fd,doc/examples/syn_registration_3d.py,,,#,48

Before Change

    warped = nipy2nifti(warped, strict=True)
    return warped, T

warped, affine_init = affine_registration(nib_static, nib_moving)
static = nib_static.get_data().squeeze().astype(np.float32)
moving = warped.get_data().squeeze().astype(np.float32)

After Change

the pyramid. The 0-th level corresponds to the finest resolution.  


opt_iter = [5, 10, 10]
registration_optimizer = SymmetricDiffeomorphicRegistration(metric, opt_iter)


Execute the optimization, which returns a DiffeomorphicMap object,
that can be used to register images back and forth between the static and moving
domains


mapping = registration_optimizer.optimize(static, moving, 
                                          static_affine, moving_affine, pre_align)


Now let"s warp the moving image and see if it gets similar to the static image

Instances