Segmentation of kidney using C-V model and anatomy priors

Jinghua Lu; Jie Chen; Juan Zhang; Wenjia Yang

doi:10.1117/12.750016

14 November 2007 Segmentation of kidney using C-V model and anatomy priors

Jinghua Lu, Jie Chen, Juan Zhang, Wenjia Yang

Proceedings Volume 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 678911 (2007) https://doi.org/10.1117/12.750016
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

This paper presents an approach for kidney segmentation on abdominal CT images as the first step of a virtual reality surgery system. Segmentation for medical images is often challenging because of the objects' complicated anatomical structures, various gray levels, and unclear edges. A coarse to fine approach has been applied in the kidney segmentation using Chan-Vese model (C-V model) and anatomy prior knowledge. In pre-processing stage, the candidate kidney regions are located. Then C-V model formulated by level set method is applied in these smaller ROI, which can reduce the calculation complexity to a certain extent. At last, after some mathematical morphology procedures, the specified kidney structures have been extracted interactively with prior knowledge. The satisfying results on abdominal CT series show that the proposed approach keeps all the advantages of C-V model and overcome its disadvantages.

Citation Download Citation

Jinghua Lu, Jie Chen, Juan Zhang, and Wenjia Yang "Segmentation of kidney using C-V model and anatomy priors", Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 678911 (14 November 2007); https://doi.org/10.1117/12.750016

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