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  4. 光电测量技术实验室
Partial sparse shape constrained sector-driven bladder wall segmentation

文献类型：期刊论文

作者Qin, Xianjing1; Lu, Hongbing3; Tian, Yan2; Yan, Pingkun2
刊名machine vision and applications
出版日期2015-07-01
卷号26期号:5页码:593-606
关键词Bladder wall segmentation Magnetic Resonance image Sparse representation Partial sparse shape Sector-driven level set
英文摘要bladder wall segmentation from magnetic resonance (mr) images plays a crucial role in clinical applications. level set-based methods are often used to extract the bladder boundaries. when suffering from the fuzzy boundaries, it often results in confused and leaking boundaries. it has been proved that an accurate shape prior can generate an effective force to address these problems. however, the shape prior estimation for the bladder is difficult due to the complex shape variations. moreover, how to constrain the level set is another challenge. in this paper, we first propose a partial sparse shape model to construct a robust shape prior. specifically, the partial reliable contour is encoded by the corresponding partial shape dictionary and decoded on the complete shape dictionary to obtain a complete reliable shape prior. second, we propose a novel sector-driven level set model for locally constraining the evolution to address the problems caused by fuzzy boundaries. our method was validated on 167 t2 fse mr images acquired from 15 different patients, better results were obtained compared to the state-of-the-art methods.
WOS标题词science & technology ; technology
类目[WOS]computer science, artificial intelligence ; computer science, cybernetics ; engineering, electrical & electronic
研究领域[WOS]computer science ; engineering
关键词[WOS]image segmentation ; deformable segmentation ; framework ; prostate ; priors
收录类别SCI ; EI
语种英语
WOS记录号WOS:000356094700003
源URL[http://ir.opt.ac.cn/handle/181661/25071]  
专题西安光学精密机械研究所_光电测量技术实验室
作者单位1.Xidian Univ Lib, Xian 710071, Shaanxi, Peoples R China
2.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
3.Fourth Mil Med Univ, Dept Biomed Engn Comp Applicat, Xian 710032, Shaanxi, Peoples R China
推荐引用方式
GB/T 7714		 Qin, Xianjing,Lu, Hongbing,Tian, Yan,et al. Partial sparse shape constrained sector-driven bladder wall segmentation[J]. machine vision and applications,2015,26(5):593-606.
APA Qin, Xianjing,Lu, Hongbing,Tian, Yan,&Yan, Pingkun.(2015).Partial sparse shape constrained sector-driven bladder wall segmentation.machine vision and applications,26(5),593-606.
MLA Qin, Xianjing,et al."Partial sparse shape constrained sector-driven bladder wall segmentation".machine vision and applications 26.5(2015):593-606.

入库方式： OAI收割

来源：西安光学精密机械研究所

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