Global and local shape analysis of the hippocampus based on level-of-detail representations

Authors:
Jeong-Sik Kim;Soo-Mi Choi;Yoo-Joo Choi;Myoung-Hee Kim
Affiliations:
School of Computer Engineering, Sejong University, Seoul, Korea;School of Computer Engineering, Sejong University, Seoul, Korea;Dept. of Computer Science and Engineering, Ewha Womans University, Seoul, Korea;Dept. of Computer Science and Engineering, Ewha Womans University, Seoul, Korea
Venue:
CIS'04 Proceedings of the First international conference on Computational and Information Science
Year:
2004

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Abstract

Both volume and shape of the organs within the brain such as hippocampus indicate their abnormal neurological states such as epilepsy, schizophrenia, and Alzheimer's diseases. This paper proposes a new method for the analysis of hippocampal shape using an integrated Octree-based representation, consisting of meshes, voxels, and skeletons. Initially, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. Then, we convert the polygonal model to intermediate binary voxel representation by a depth-buffer based voxelization, which makes it easier to extract a 3-D skeleton as well as relate to original MR images. As a similarity measure between the shapes, we compute L2 norm and Hausdorff distance for each sampled mesh by shooting the rays fired from the extracted skeleton. It also allows an interactive analysis because of the octree-based data structure. Moreover, it increases the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.