Jeong Sik Kim , Soo Mi Choi , Yoo Ju Choi , Myoung Hee Kim

The KIPS Transactions:PartA, Vol. 11, No. 7, pp. 555-562, Dec. 2004
10.3745/KIPSTA.2004.11.7.555,   PDF Download:

Abstract

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation, And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute I2 Norm and Hausdorff distance for each sampled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape interactivelty, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to descriminate the changes between local shapes of hippocampus and more over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.

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