Evaluation of Moving Least Squares as a Technique for Non-Rigid Medical Image Registration

Abstract

Abstract

This thesis evaluates the performance of two non-rigid image registration techniques. The Moving Least Squares (MLS) technique is compared to the widely used Thin-plate Spline (TPS) method. Both methods interpolate a set of fiducial points in registering two images. An attractive feature of the MLS method is that it seeks to minimize local scaling and shearing, producing a global transformation that is as rigid as possible. The MLS and TPS techniques are applied to two- and three-dimensional medical images. Both qualitative and quantitative comparisons are presented. The two techniques are quantitatively evaluated by computing target registration errors (TREs) at selected points of interest. Our results indicate that the MLS algorithm performs better than the TPS method with lower TRE values and visually better registered images, indicating that MLS may be a better candidate for registration tasks when rigid registration is insufficient but the deformation field is sought to be minimal.