3-D diffeomorphic shape registration on hippocampal data sets.

Hongyu Guo; Anand Rangarajan; Sarang C Joshi

doi:10.1007/11566489_121

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3-D diffeomorphic shape registration on hippocampal data sets.

Hongyu Guo·Anand Rangarajan·Sarang C Joshi

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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.

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Algorithms Artificial Intelligence Diagnosis, Differential Epilepsy, Temporal Lobe Hippocampus Humans Image Enhancement Image Interpretation, Computer-Assisted Imaging, Three-Dimensional Magnetic Resonance Imaging Pattern Recognition, Automated Reproducibility of Results Sensitivity and Specificity Subtraction Technique Evaluation Study Journal Article

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Hongyu Guo, Anand Rangarajan, Sarang C Joshi. 2005. 3-D diffeomorphic shape registration on hippocampal data sets.. https://doi.org/10.1007/11566489_121

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