{"title":"An improved multi-resolution 2D/3D registration method","authors":"Yipei Cao, Fei He, Feng Qu, Tiejun Wang, Chen Yang, Weili Shi, Zhengang Jiang","doi":"10.1109/cvidliccea56201.2022.9824315","DOIUrl":null,"url":null,"abstract":"2D/3D image registration is one of the key technologies to realize pose estimation in computer-aided surgery. In order to improve the global and local search performance of the model in the pose parameter space, an improved multi-resolution 2D/3D registration method is proposed in this paper. Firstly, aiming at the problem that the intensity-based similarity measure is not sensitive to small offset between images, the gradient information with strong sensitivity to image texture edge is introduced, and the Intensity and Gradient Weighted Correlation (IGWC) coefficient similarity measure is proposed; Secondly, aiming at the problem of slow convergence of global optimization algorithm and small capture range of local optimization algorithm, a global-local combined registration optimization strategy is proposed. The experimental results show that this method improves the registration accuracy and success rate.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"28 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/cvidliccea56201.2022.9824315","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
2D/3D image registration is one of the key technologies to realize pose estimation in computer-aided surgery. In order to improve the global and local search performance of the model in the pose parameter space, an improved multi-resolution 2D/3D registration method is proposed in this paper. Firstly, aiming at the problem that the intensity-based similarity measure is not sensitive to small offset between images, the gradient information with strong sensitivity to image texture edge is introduced, and the Intensity and Gradient Weighted Correlation (IGWC) coefficient similarity measure is proposed; Secondly, aiming at the problem of slow convergence of global optimization algorithm and small capture range of local optimization algorithm, a global-local combined registration optimization strategy is proposed. The experimental results show that this method improves the registration accuracy and success rate.