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Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images
Li, Guodong1; Chen, Xinjian2; Shi, Fei2; Zhu, Weifang2; Tian, Jie1; Xiang, Dehui2
2015-12-01
发表期刊IEEE TRANSACTIONS ON IMAGE PROCESSING
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
DOI10.1109/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:31[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
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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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