{"title":"利用纹理控制实现二维/三维差分多模态图像配准的三阶段方法","authors":"Ke Chen, Huan Han","doi":"10.1137/23m1583971","DOIUrl":null,"url":null,"abstract":"SIAM Journal on Imaging Sciences, Volume 17, Issue 3, Page 1690-1728, September 2024. <br/> Abstract.Intensity inhomogeneity is a challenging task in image registration. Few past works have addressed the case of intensity inhomogeneity due to texture noise. To address this difficulty, we propose a novel three-stage approach for 2D/3D diffeomorphic multimodality image registration. The proposed approach contains three stages: (1) [math] decomposition which decomposes the image pairs into texture, noise, and smooth component; (2) Blake–Zisserman homogenization which transforms the geometric features from different modalities into approximately the same modality in terms of the first-order and second-order edge information; (3) image registration which combines the homogenized geometric features and mutual information. Based on the proposed approach, the greedy matching for multimodality image registration is discussed and a coarse-to-fine algorithm is also proposed. Furthermore, several numerical tests are performed to validate the efficiency of the proposed approach.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Three-Stage Approach for 2D/3D Diffeomorphic Multimodality Image Registration with Textural Control\",\"authors\":\"Ke Chen, Huan Han\",\"doi\":\"10.1137/23m1583971\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"SIAM Journal on Imaging Sciences, Volume 17, Issue 3, Page 1690-1728, September 2024. <br/> Abstract.Intensity inhomogeneity is a challenging task in image registration. Few past works have addressed the case of intensity inhomogeneity due to texture noise. To address this difficulty, we propose a novel three-stage approach for 2D/3D diffeomorphic multimodality image registration. The proposed approach contains three stages: (1) [math] decomposition which decomposes the image pairs into texture, noise, and smooth component; (2) Blake–Zisserman homogenization which transforms the geometric features from different modalities into approximately the same modality in terms of the first-order and second-order edge information; (3) image registration which combines the homogenized geometric features and mutual information. Based on the proposed approach, the greedy matching for multimodality image registration is discussed and a coarse-to-fine algorithm is also proposed. Furthermore, several numerical tests are performed to validate the efficiency of the proposed approach.\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1137/23m1583971\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1137/23m1583971","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Three-Stage Approach for 2D/3D Diffeomorphic Multimodality Image Registration with Textural Control
SIAM Journal on Imaging Sciences, Volume 17, Issue 3, Page 1690-1728, September 2024. Abstract.Intensity inhomogeneity is a challenging task in image registration. Few past works have addressed the case of intensity inhomogeneity due to texture noise. To address this difficulty, we propose a novel three-stage approach for 2D/3D diffeomorphic multimodality image registration. The proposed approach contains three stages: (1) [math] decomposition which decomposes the image pairs into texture, noise, and smooth component; (2) Blake–Zisserman homogenization which transforms the geometric features from different modalities into approximately the same modality in terms of the first-order and second-order edge information; (3) image registration which combines the homogenized geometric features and mutual information. Based on the proposed approach, the greedy matching for multimodality image registration is discussed and a coarse-to-fine algorithm is also proposed. Furthermore, several numerical tests are performed to validate the efficiency of the proposed approach.