3-D diffeomorphic shape registration on hippocampal data sets

Authors:
Hongyu Guo;Anand Rangarajan;Sarang C. Joshi
Affiliations:
Dept. of CAMS, Texas A&M University-Corpus Christi;Dept. of CISE, University of Florida;Dept. of Radiation Oncology, University of North Carolina at Chapel Hill
Venue:
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Year:
2005

Citing 10
Cited 2

Active shape models—their training and application

Computer Vision and Image Understanding
Sequential Operations in Digital Picture Processing

Journal of the ACM (JACM)
Kernel Fisher for Shape Based Classification in Epilepsy

MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Geodesic Interpolating Splines

EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Learning an Atlas from Unlabeled Point-Sets

MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
A new point matching algorithm for non-rigid registration

Computer Vision and Image Understanding - Special issue on nonrigid image registration
A New Joint Clustering and Diffeomorphism Estimation Algorithm for Non-Rigid Shape Matching

CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 1 - Volume 01
Diffeomorphic matching of distributions: a new approach for unlabelled point-sets and sub-manifolds matching

CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A new metric for probability distributions

IEEE Transactions on Information Theory
Landmark matching via large deformation diffeomorphisms

IEEE Transactions on Image Processing

Group-Wise Point-Set Registration Using a Novel CDF-Based Havrda-Charvát Divergence

International Journal of Computer Vision
Deformable density matching for 3D non-rigid registration of shapes

MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.