{"title":"活动区域分割的有限元变形网格","authors":"K. Popuri, Dana Cobzas, Martin Jägersand","doi":"10.1109/ISBI.2013.6556673","DOIUrl":null,"url":null,"abstract":"We propose a novel template-based multi-region segmentation method using a finite element method (FEM) deformation model with diffusion-based regularization. Our proposed method is computationally more efficient than the traditional template-based segmentation methods that use non-parametric or B-spline based deformation models, as it significantly reduces the number of degrees of freedom (DOF) associated with the energy minimization that arises in template-based segmentation. Further, like all template-based segmentation approaches our method is able to preserve topology of the initial regions of interest (ROIs) defined in the template, which is very useful for segmentation of anatomical structures. Segmentation results on medical images with various anatomical structures show that the proposed method improves computational efficiency without compromising segmentation accuracy.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A FEM deformable mesh for active region segmentation\",\"authors\":\"K. Popuri, Dana Cobzas, Martin Jägersand\",\"doi\":\"10.1109/ISBI.2013.6556673\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel template-based multi-region segmentation method using a finite element method (FEM) deformation model with diffusion-based regularization. Our proposed method is computationally more efficient than the traditional template-based segmentation methods that use non-parametric or B-spline based deformation models, as it significantly reduces the number of degrees of freedom (DOF) associated with the energy minimization that arises in template-based segmentation. Further, like all template-based segmentation approaches our method is able to preserve topology of the initial regions of interest (ROIs) defined in the template, which is very useful for segmentation of anatomical structures. Segmentation results on medical images with various anatomical structures show that the proposed method improves computational efficiency without compromising segmentation accuracy.\",\"PeriodicalId\":178011,\"journal\":{\"name\":\"2013 IEEE 10th International Symposium on Biomedical Imaging\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 10th International Symposium on Biomedical Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISBI.2013.6556673\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 10th International Symposium on Biomedical Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2013.6556673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A FEM deformable mesh for active region segmentation
We propose a novel template-based multi-region segmentation method using a finite element method (FEM) deformation model with diffusion-based regularization. Our proposed method is computationally more efficient than the traditional template-based segmentation methods that use non-parametric or B-spline based deformation models, as it significantly reduces the number of degrees of freedom (DOF) associated with the energy minimization that arises in template-based segmentation. Further, like all template-based segmentation approaches our method is able to preserve topology of the initial regions of interest (ROIs) defined in the template, which is very useful for segmentation of anatomical structures. Segmentation results on medical images with various anatomical structures show that the proposed method improves computational efficiency without compromising segmentation accuracy.