{"title":"Deformable models for 3-D medical images using finite elements and balloons","authors":"L. Cohen, I. Cohen","doi":"10.1109/CVPR.1992.223130","DOIUrl":null,"url":null,"abstract":"A 3-D generalization of the balloon model as a 3-D deformable surface, which evolves in 3-D images, is presented. It is deformed under the action of internal and external forces attracting the surface toward detected edge elements by means of an attraction potential. To solve the minimization problem for a surface, two simplified approaches are shown, defining a 3-D surface as a series of 2-D planar curves. Then the 3-D model is solved using the finite-element method, yielding greater stability and faster convergence. This model has been used to segment magnetic resonance images.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"2002 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"94","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1992.223130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 94
Abstract
A 3-D generalization of the balloon model as a 3-D deformable surface, which evolves in 3-D images, is presented. It is deformed under the action of internal and external forces attracting the surface toward detected edge elements by means of an attraction potential. To solve the minimization problem for a surface, two simplified approaches are shown, defining a 3-D surface as a series of 2-D planar curves. Then the 3-D model is solved using the finite-element method, yielding greater stability and faster convergence. This model has been used to segment magnetic resonance images.<>