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Proceedings Paper

A novel automatic segmentation of the left ventricle cavity and myocardium in MSCT data
Author(s): Xingjia Wang; Lina Dong; Yufeng Huang; Chuanfu Li; Huanqing Feng
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Paper Abstract

The manual segmentation of 3D high resolution cardiac multi slice CT (MSCT) datasets is both labor intensive and time consuming. Therefore, it is necessary to provide a powerful automatic/semi-automatic method to segmentation the cardiac myocardium and cavities. In this paper a novel approach for the automatic 3D segmentation has been developed to extract the epicardium and endocardium boundaries of the left ventricle (LV) of the heart. The segmentation of the MSCT data is divided into three parts. The first part, which is based on nonlinear intensity transformation and bilateral filter, paints background and smoothes slice for all real CT images; The second part, applies a cavity template mask to extract the LV cavity coarse region from all slices using the threshold and morphologic operations; The last part performs improved coupled level set algorithm incorporating coarse cavity contours and priors for the final segmentation. Experimental results and 3D surface reconstruction show the efficacy and advantage of our method for the segmentation of the left ventricle from real CT data.

Paper Details

Date Published: 19 August 2010
PDF: 8 pages
Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78200K (19 August 2010); doi: 10.1117/12.867463
Show Author Affiliations
Xingjia Wang, Univ. of Science and Technology of China (China)
Lina Dong, Univ. of Science and Technology of China (China)
Yufeng Huang, Univ. of Science and Technology of China (China)
Chuanfu Li, Anhui College of Traditional Chinese Medicine (China)
Huanqing Feng, Univ. of Science and Technology of China (China)


Published in SPIE Proceedings Vol. 7820:
International Conference on Image Processing and Pattern Recognition in Industrial Engineering
Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du, Editor(s)

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