Partial sparse shape constrained sector-driven bladder wall segmentation

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光电测量技术实验室

	Partial sparse shape constrained sector-driven bladder wall segmentation
	Qin, Xianjing 1; Lu, Hongbing 3; Tian, Yan2 ; Yan, Pingkun 2
刊名	machine vision and applications
	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
内容类型	期刊论文
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.