| Partial sparse shape constrained sector-driven bladder wall segmentation | |
Qin, Xianjing1; Lu, Hongbing3; Tian, Yan2 ; Yan, Pingkun2
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| 2015-07-01 | |
| 发表期刊 | MACHINE VISION AND APPLICATIONS
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| 卷号 | 26期号:5页码:593-606 |
| 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. |
| 文章类型 | Article |
| 关键词 | Bladder Wall Segmentation Magnetic Resonance Image Sparse Representation Partial Sparse Shape Sector-driven Level Set |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1007/s00138-015-0684-z |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | IMAGE SEGMENTATION ; DEFORMABLE SEGMENTATION ; FRAMEWORK ; PROSTATE ; PRIORS |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Cybernetics ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000356094700003 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/25071 |
| 专题 | 光电跟踪与测量技术研究室 |
| 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. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Partial sparse shape（3779KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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