Adaptive Shape Prior Constrained Level Sets for Bladder MR Image Segmentation

doi:10.1109/JBHI.2013.2288935

OPT OpenIR > 光谱成像技术研究室

	Adaptive Shape Prior Constrained Level Sets for Bladder MR Image Segmentation
	Qin, Xianjing 1; Li, Xuelong2 ; Liu, Yang 3; Lu, Hongbing 3; Yan, Pingkun 1
作者部门	光学影像学习与分析中心
	2014-09-01
发表期刊	IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
ISSN	2168-2194
卷号	18 期号:5 页码:1707-1716
产权排序	1
摘要	Three-dimensional bladder wall segmentation for thickness measuring can be very useful for bladder magnetic resonance (MR) image analysis, since thickening of the bladder wall can indicate abnormality. However, it is a challenging task due to the artifacts inside bladder lumen, weak boundaries in the apex and base areas, and complicated outside intensity distributions. To deal with these difficulties, in this paper, an adaptive shape prior constrained directional level set model is proposed to segment the inner and outer boundaries of the bladder wall. In addition, a coupled directional level set model is presented to refine the segmentation by exploiting the prior knowledge of region information and minimum thickness. With our proposed method, the influence of the artifacts in the bladder lumen and the complicated outside tissues surrounding the bladder can be appreciably reduced. Furthermore, the leakage on the weak boundaries can be avoided. Compared with other related methods, better results were obtained on 11 patients' 3-D bladder MR images by using the proposed method.
文章类型	Article
关键词	Adaptive Shape Prior (Asp) Coupled Level Sets Directional Gradient Segmentation
WOS标题词	Science & Technology ; Technology ; Life Sciences & Biomedicine
DOI	10.1109/JBHI.2013.2288935
收录类别	SCI ; EI
关键词[WOS]	ACTIVE CONTOURS ; EVOLUTION ; WALL ; CT
语种	英语
WOS研究方向	Computer Science ; Mathematical & Computational Biology ; Medical Informatics
WOS类目	Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications ; Mathematical & Computational Biology ; Medical Informatics
WOS记录号	WOS:000341986600021
引用统计	被引频次：47[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/22350
专题	光谱成像技术研究室
作者单位	1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China 2.Chinese Acad Sci, Ctr Opt Imagery Anal & Learning, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China 3.Fourth Mil Med Univ, Dept Biomed Engn Comp Applicat, Xian 710032, Peoples R China
推荐引用方式 GB/T 7714	Qin, Xianjing,Li, Xuelong,Liu, Yang,et al. Adaptive Shape Prior Constrained Level Sets for Bladder MR Image Segmentation[J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,2014,18(5):1707-1716.
APA	Qin, Xianjing,Li, Xuelong,Liu, Yang,Lu, Hongbing,&Yan, Pingkun.(2014).Adaptive Shape Prior Constrained Level Sets for Bladder MR Image Segmentation.IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,18(5),1707-1716.
MLA	Qin, Xianjing,et al."Adaptive Shape Prior Constrained Level Sets for Bladder MR Image Segmentation".IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 18.5(2014):1707-1716.

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