NDLI: Left ventricle segmentation from MSCT data based on random walks approach

Content Provider	IEEE Xplore Digital Library
Author	Lina Dong Xingjia Wang Tong Tong Huanqing Feng Heqin Zhou Chuanfu Li
Copyright Year	2010
Description	Author affiliation: Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, China (Lina Dong; Xingjia Wang; Tong Tong; Huanqing Feng) \|\| Department of Automation, University of Science and Technology of China, Hefei, Anhui 230027, China (Heqin Zhou) \|\| Medical Image Center, the First, Affiliated Hospital, Anhui Traditional Medicine College, Hefei, Anhui 230031, China (Chuanfu Li)
Abstract	Cardiovascular diseases (CVDs) continue to be the number one cause of death globally. Functions evaluation of left ventricle (LV), especially ejection fraction (EF) and mass, is the significant predictor of CVDs. Taking the place of extremely time-consuming manual segmentation, accurate extraction of the cavity and myocardium of LV is the key step for analyzing heart functions quantitatively. In this paper, an improved robust semi-automated approach is presented for segmentation of cavity and myocardium from 3D cardiac multi-slice CT (MSCT) dataset. Based on random walks, a novel seeds selection method composed of region growing technique and morphological operation is introduced to locate and identify the cavity and myocardium of LV. 6-connected lattice topology and Conjugate Gradient method have been applied in the random walker algorithm to promote the segmentation performance of 3D dataset. The consecutive result of 3D reconstruction shows the efficacy and advantage of our method for the segmentation of LV in MSCT images.
Starting Page	157
Ending Page	161
File Size	428351
Page Count	5
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5646393
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gradient methods random walks seeds selection Lattices Image segmentation left ventricle (LV) MSCT Conjugate Gradient method Myocardium segmentation Three dimensional displays Cavity resonators region growing Biomedical imaging
Content Type	Text
Resource Type	Article

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