{"title":"图像重建的有界误差估计方法","authors":"Ying Zhang, A. Hero, W. Rogers","doi":"10.1109/NSSMIC.1992.301091","DOIUrl":null,"url":null,"abstract":"A bounded error (BE) approach to image reconstruction is investigated. In this approach a bound on the measured projections errors is specified and the set of images which is consistent with both the data and the error bound is constructed. The error bound can account for both statistical noise uncertainty, e.g., due to randoms correction or other Poisson-destructive preprocessing, and model uncertainty, e.g., due to a mismodeled or uncalibrated system matrix. The consistent set of images is a set estimate of the image from which point estimates, i.e., image reconstructions can be selected.<<ETX>>","PeriodicalId":447239,"journal":{"name":"IEEE Conference on Nuclear Science Symposium and Medical Imaging","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A bounded error estimation approach to image reconstruction\",\"authors\":\"Ying Zhang, A. Hero, W. Rogers\",\"doi\":\"10.1109/NSSMIC.1992.301091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A bounded error (BE) approach to image reconstruction is investigated. In this approach a bound on the measured projections errors is specified and the set of images which is consistent with both the data and the error bound is constructed. The error bound can account for both statistical noise uncertainty, e.g., due to randoms correction or other Poisson-destructive preprocessing, and model uncertainty, e.g., due to a mismodeled or uncalibrated system matrix. The consistent set of images is a set estimate of the image from which point estimates, i.e., image reconstructions can be selected.<<ETX>>\",\"PeriodicalId\":447239,\"journal\":{\"name\":\"IEEE Conference on Nuclear Science Symposium and Medical Imaging\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Conference on Nuclear Science Symposium and Medical Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NSSMIC.1992.301091\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Conference on Nuclear Science Symposium and Medical Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSSMIC.1992.301091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A bounded error estimation approach to image reconstruction
A bounded error (BE) approach to image reconstruction is investigated. In this approach a bound on the measured projections errors is specified and the set of images which is consistent with both the data and the error bound is constructed. The error bound can account for both statistical noise uncertainty, e.g., due to randoms correction or other Poisson-destructive preprocessing, and model uncertainty, e.g., due to a mismodeled or uncalibrated system matrix. The consistent set of images is a set estimate of the image from which point estimates, i.e., image reconstructions can be selected.<>
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