A new tissue segmentation algorithm in 3D data based on boundary model and local character structure

Yan-jun Peng; Yuan-hong Wang; Jiao-ying Shi

doi:10.1117/12.655222

3 November 2005 A new tissue segmentation algorithm in 3D data based on boundary model and local character structure

Yan-jun Peng, Yuan-hong Wang, Jiao-ying Shi

Proceedings Volume 6044, MIPPR 2005: Image Analysis Techniques; 60441J (2005) https://doi.org/10.1117/12.655222
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

Abstract

Tissue segmentation in 3d data is an important technology in medical visualization, image segmentation and virtual endoscopy. It is difficulty to automatically and accurately implement tissue segmentation in 3d data because of its complexity. A semi-automatic tissue segmentation algorithm in 3d data is proposed based on boundary model and local character structure in this paper. We found out inner voexls and outer voexls by pre-appointed voxel based on boundary model. And then, boundary voexls are correctly classified into different tissues by their eigenvalues of Hessian matrix based on the local character structure. Only eigenvalues of the boundary voxels are computed, so little time is used compared with other algorithms based on local character structure. It can quickly and effectively realize the segmentation of single tissue.

Citation Download Citation

Yan-jun Peng, Yuan-hong Wang, and Jiao-ying Shi "A new tissue segmentation algorithm in 3D data based on boundary model and local character structure", Proc. SPIE 6044, MIPPR 2005: Image Analysis Techniques, 60441J (3 November 2005); https://doi.org/10.1117/12.655222

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