Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images

doi:10.1109/TIP.2015.2481326

	Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images
	Li, Guodong1 ; Chen, Xinjian 2; Shi, Fei 2; Zhu, Weifang 2; Tian, Jie 1; Xiang, Dehui 2
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING
	2015-12-01
卷号	24 期号:12 页码:5315-5329
文章类型	Article
摘要	Liver segmentation is still a challenging task in medical image processing area due to the complexity of the liver's anatomy, low contrast with adjacent organs, and presence of pathologies. This investigation was used to develop and validate an automated method to segment livers in CT images. The proposed framework consists of three steps: 1) preprocessing; 2) initialization; and 3) segmentation. In the first step, a statistical shape model is constructed based on the principal component analysis and the input image is smoothed using curvature anisotropic diffusion filtering. In the second step, the mean shape model is moved using thresholding and Euclidean distance transformation to obtain a coarse position in a test image, and then the initial mesh is locally and iteratively deformed to the coarse boundary, which is constrained to stay close to a subspace of shapes describing the anatomical variability. Finally, in order to accurately detect the liver surface, deformable graph cut was proposed, which effectively integrates the properties and interrelationship of the input images and initialized surface. The proposed method was evaluated on 50 CT scan images, which are publicly available in two databases Sliver07 and 3Dircadb. The experimental results showed that the proposed method was effective and accurate for detection of the liver surface.
关键词	Liver Segmentation Principal Component Analysis Euclidean Distance Transformation Deformable Graph Cut
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TIP.2015.2481326
关键词[WOS]	MODEL ; TOMOGRAPHY ; LAPLACIAN
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000362488900016
引用统计	被引频次：134[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/10031
专题	中国科学院分子影像重点实验室
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Soochow Univ, Sch Elect & Informat Engn, Suzhou 215006, Jiangsu, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Li, Guodong,Chen, Xinjian,Shi, Fei,et al. Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015,24(12):5315-5329.
APA	Li, Guodong,Chen, Xinjian,Shi, Fei,Zhu, Weifang,Tian, Jie,&Xiang, Dehui.(2015).Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images.IEEE TRANSACTIONS ON IMAGE PROCESSING,24(12),5315-5329.
MLA	Li, Guodong,et al."Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images".IEEE TRANSACTIONS ON IMAGE PROCESSING 24.12(2015):5315-5329.

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