Computer vision for biomedical image applications : first international workshop, CVBIA 2005, Beijing, China, October 21, 2005 : proceedings. CVBIA 2005 (2005 : Beijing, China)最新文献

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Simultaneous Segmentation and Motion Recovery in 3D Cardiac Image Analysis 三维心脏图像分析中的同步分割和运动恢复
Zhuang Ling, Huafeng Liu, Wei Chen, H. Bao, P. Shi
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引用次数: 2
Spatial and Temporal Analysis for Optical Imaging Data Using CWT and tICA 基于CWT和tICA的光学成像数据时空分析
Yadong Liu, Guohua Zang, Fayi Liu, Lirong Yan, Ming Li, Zongtan Zhou, D. Hu
{"title":"Spatial and Temporal Analysis for Optical Imaging Data Using CWT and tICA","authors":"Yadong Liu, Guohua Zang, Fayi Liu, Lirong Yan, Ming Li, Zongtan Zhou, D. Hu","doi":"10.1007/11569541_51","DOIUrl":"https://doi.org/10.1007/11569541_51","url":null,"abstract":"","PeriodicalId":91857,"journal":{"name":"Computer vision for biomedical image applications : first international workshop, CVBIA 2005, Beijing, China, October 21, 2005 : proceedings. CVBIA 2005 (2005 : Beijing, China)","volume":"49 1","pages":"508-516"},"PeriodicalIF":0.0,"publicationDate":"2005-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85799204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Shape Based Segmentation of Anatomical Structures in Magnetic Resonance Images. 基于形状的磁共振图像解剖结构分割法
Kilian M Pohl, John Fisher, Ron Kikinis, W Eric L Grimson, William M Wells
{"title":"Shape Based Segmentation of Anatomical Structures in Magnetic Resonance Images.","authors":"Kilian M Pohl, John Fisher, Ron Kikinis, W Eric L Grimson, William M Wells","doi":"10.1007/11569541_49","DOIUrl":"10.1007/11569541_49","url":null,"abstract":"<p><p>Standard image based segmentation approaches perform poorly when there is little or no contrast along boundaries of different regions. In such cases, segmentation is largely performed manually using prior knowledge of the shape and relative location of the underlying structures combined with partially discernible boundaries. We present an automated approach guided by covariant shape deformations of neighboring structures, which is an additional source of prior information. Captured by a shape atlas, these deformations are transformed into a statistical model using the logistic function. Structure boundaries, anatomical labels, and image inhomogeneities are estimated simultaneously within an Expectation-Maximization formulation of the maximum a posteriori probability estimation problem. We demonstrate the approach on 20 brain magnetic resonance images showing superior performance, particularly in cases where purely image based methods fail.</p>","PeriodicalId":91857,"journal":{"name":"Computer vision for biomedical image applications : first international workshop, CVBIA 2005, Beijing, China, October 21, 2005 : proceedings. CVBIA 2005 (2005 : Beijing, China)","volume":"3765 ","pages":"489-498"},"PeriodicalIF":0.0,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5486153/pdf/nihms861376.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35131094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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