Improving image registration by correspondence interpolation

This paper presents how using a correspondence-based interpolation scheme for 3D image registration improves the registration accuracy. The interpolator takes into account correspondences across slices, which is an advantage, particularly when the volume has thick slices, and where anatomies lie non-parallel to the slice direction. We use our previously presented approach for correspondence-based interpolation and demonstrate results on two different datasets, brain and cardiac MRI. The results are evaluated (i) qualitatively by examination of gradient images and cardiac pig atlases and (ii) quantitatively by registering downsampled brain data using two different interpolators and subsequently applying the deformation fields to the original data. The results show that the interpolator provides better gradient images and a more sharp cardiac atlas. Moreover, it provides better deformation fields on downsampled data, increasing the registration accuracy of original data to 5.8% on average with respect to a standard interpolator.