{"title":"支架移除以改善2D-3D配准","authors":"Maximilian Baust, S. Demirci, Nassir Navab","doi":"10.1109/ISBI.2009.5193277","DOIUrl":null,"url":null,"abstract":"Being performed under extensive radiation exposure, endovascular stent graft placements would greatly benefit from a reliable navigation solution. A successful implementation of such a system requires an accurate 2D–3D registration. Since the stent graft is only visible in the radiograph, registration algorithms can easily be attracted to wrong structures. In this paper, we address this problem by presenting a fast algorithm for removing the stent graft which meets real-time constraints. Based on Poisson editing, our method is easy to implement and extremely user-friendly as it requires neither parameter adjustment nor precise presegmentation. Moreover, we prove the significance of our algorithm by a realistic ground truth study.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Stent graft removal for improving 2D–3D registration\",\"authors\":\"Maximilian Baust, S. Demirci, Nassir Navab\",\"doi\":\"10.1109/ISBI.2009.5193277\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Being performed under extensive radiation exposure, endovascular stent graft placements would greatly benefit from a reliable navigation solution. A successful implementation of such a system requires an accurate 2D–3D registration. Since the stent graft is only visible in the radiograph, registration algorithms can easily be attracted to wrong structures. In this paper, we address this problem by presenting a fast algorithm for removing the stent graft which meets real-time constraints. Based on Poisson editing, our method is easy to implement and extremely user-friendly as it requires neither parameter adjustment nor precise presegmentation. Moreover, we prove the significance of our algorithm by a realistic ground truth study.\",\"PeriodicalId\":272938,\"journal\":{\"name\":\"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISBI.2009.5193277\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2009.5193277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stent graft removal for improving 2D–3D registration
Being performed under extensive radiation exposure, endovascular stent graft placements would greatly benefit from a reliable navigation solution. A successful implementation of such a system requires an accurate 2D–3D registration. Since the stent graft is only visible in the radiograph, registration algorithms can easily be attracted to wrong structures. In this paper, we address this problem by presenting a fast algorithm for removing the stent graft which meets real-time constraints. Based on Poisson editing, our method is easy to implement and extremely user-friendly as it requires neither parameter adjustment nor precise presegmentation. Moreover, we prove the significance of our algorithm by a realistic ground truth study.