Nonrigid Medical Image Registration Based on Curves

Abstract

Medical image registration is the process of aligning two or more images in such a way that its anatomical structures properly overlap each other in a common spatial domain and resultant 3D images can be used for diagnosis and therapy by surgeons. A number of nonlinear methods have been developed for inter-subject and intra-subject 3D medical image registration. This paper is a part of research experiments which uses the Fast Radial Basis Function (RBF) technique for nonrigid registration of 3D medical images. The technique is a point-based registration evaluation algorithm which registers MR or CT images in less than a second with no compromise on accuracy as compared to standard RBF-based methods. Further we demonstrate that the accuracy of the registration improves when using increasingly more salient feature points (i.e. point landmarks and a few external curves) without affecting the speed of the algorithm. External curves are extracted using a combined watershed and active contours algorithm. Our results show that both accuracy and speed of the Fast Radial Basis algorithm is improved on intra-subject registration of MR image datasets obtained from the Vanderbilt Database as compared to the standard competing methods.