3-D diffeomorphic shape registration on hippocampal data sets.
Matching 3D shapes is important in many medical imaging applications. We show that a joint clustering and diffeomorphism estimation strategy is capable of simultaneously estimating correspondences and a diffeomorphism between unlabeled 3D point-sets. Correspondence is established between the cluster centers and this is coupled with a simultaneous estimation of a 3D diffeomorphism of space. The number of clusters can be estimated by minimizing the Jensen-Shannon divergence on the registered data. We apply our algorithm to both synthetically warped 3D hippocampal shapes as well as real 3D hippocampal shapes from different subjects.
Guo
Hongyu
H
Dept. of CAMS, Texas A&M University-Corpus Christi, USA.
Rangarajan
Anand
A
Joshi
Sarang C
SC