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Prostate Segmentation in MR Images Using Discriminant Boundary Features

文献类型：期刊论文

作者Yang, Meijuan1; Li, Xuelong1; Turkbey, Baris2; Choyke, Peter L.2; Yan, Pingkun1
刊名ieee transactions on biomedical engineering
出版日期2013-02-01
卷号60期号:2页码:479-488
关键词Discriminant analysis image feature prostate segmentation statistical shape model (SSM)
英文摘要segmentation of the prostate in magnetic resonance image has become more in need for its assistance to diagnosis and surgical planning of prostate carcinoma. due to the natural variability of anatomical structures, statistical shape model has been widely applied in medical image segmentation. robust and distinctive local features are critical for statistical shape model to achieve accurate segmentation results. the scale invariant feature transformation (sift) has been employed to capture the information of the local patch surrounding the boundary. however, when sift feature being used for segmentation, the scale and variance are not specified with the location of the point of interest. to deal with it, the discriminant analysis in machine learning is introduced to measure the distinctiveness of the learned sift features for each landmark directly and to make the scale and variance adaptive to the locations. as the gray values and gradients vary significantly over the boundary of the prostate, separate appearance descriptors are built for each landmark and then optimized. after that, a two stage coarse-to-fine segmentation approach is carried out by incorporating the local shape variations. finally, the experiments on prostate segmentation from mr image are conducted to verify the efficiency of the proposed algorithms.
WOS标题词science & technology ; technology
类目[WOS]engineering, biomedical
研究领域[WOS]engineering
关键词[WOS]active shape model ; ct images ; appearance
收录类别SCI ; EI
语种英语
WOS记录号WOS:000316809800024
公开日期2015-06-30
源URL[http://ir.opt.ac.cn/handle/181661/23454]  
专题西安光学精密机械研究所_光学影像学习与分析中心
作者单位1.Chinese Acad Sci, Ctr OPT IMagery Anal & Learning, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China
2.NCI, NIH, Bethesda, MD 20892 USA
推荐引用方式
GB/T 7714		 Yang, Meijuan,Li, Xuelong,Turkbey, Baris,et al. Prostate Segmentation in MR Images Using Discriminant Boundary Features[J]. ieee transactions on biomedical engineering,2013,60(2):479-488.
APA Yang, Meijuan,Li, Xuelong,Turkbey, Baris,Choyke, Peter L.,&Yan, Pingkun.(2013).Prostate Segmentation in MR Images Using Discriminant Boundary Features.ieee transactions on biomedical engineering,60(2),479-488.
MLA Yang, Meijuan,et al."Prostate Segmentation in MR Images Using Discriminant Boundary Features".ieee transactions on biomedical engineering 60.2(2013):479-488.

入库方式： OAI收割

来源：西安光学精密机械研究所

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