Lifeng Yu, D. Xia, Y. Zou, E. Sidky, Xiaochuan Pan, C. Pelizzari
{"title":"一种改进噪声特性的扇形波束CT感兴趣区域重建反投影滤波算法","authors":"Lifeng Yu, D. Xia, Y. Zou, E. Sidky, Xiaochuan Pan, C. Pelizzari","doi":"10.1109/NSSMIC.2005.1596893","DOIUrl":null,"url":null,"abstract":"We propose an alternative backprojection-filtration(BPF)-based reconstruction algorithm for fan-beam CT, which reconstructs images by first converting the fan-beam data to fan-parallel-beam data and then using a modified parallel-beam BPF algorithm to obtain the reconstruction. This proposed algorithm retains the properties of the original fan-beam BPF algorithm in that it can reconstruct exact region of interest (ROI) images from truncated data and/or super-short-scan data. The major advantage of this algorithm is its improved noise properties because of the elimination of the spatially-variant weighting factor. In addition, the proposed algorithm is computationally more efficient","PeriodicalId":105619,"journal":{"name":"IEEE Nuclear Science Symposium Conference Record, 2005","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A rebinning-type backprojection-filtration algorithm for region of interest reconstruction in fan-beam CT with improved noise properties\",\"authors\":\"Lifeng Yu, D. Xia, Y. Zou, E. Sidky, Xiaochuan Pan, C. Pelizzari\",\"doi\":\"10.1109/NSSMIC.2005.1596893\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose an alternative backprojection-filtration(BPF)-based reconstruction algorithm for fan-beam CT, which reconstructs images by first converting the fan-beam data to fan-parallel-beam data and then using a modified parallel-beam BPF algorithm to obtain the reconstruction. This proposed algorithm retains the properties of the original fan-beam BPF algorithm in that it can reconstruct exact region of interest (ROI) images from truncated data and/or super-short-scan data. The major advantage of this algorithm is its improved noise properties because of the elimination of the spatially-variant weighting factor. In addition, the proposed algorithm is computationally more efficient\",\"PeriodicalId\":105619,\"journal\":{\"name\":\"IEEE Nuclear Science Symposium Conference Record, 2005\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Nuclear Science Symposium Conference Record, 2005\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NSSMIC.2005.1596893\",\"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 Nuclear Science Symposium Conference Record, 2005","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSSMIC.2005.1596893","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A rebinning-type backprojection-filtration algorithm for region of interest reconstruction in fan-beam CT with improved noise properties
We propose an alternative backprojection-filtration(BPF)-based reconstruction algorithm for fan-beam CT, which reconstructs images by first converting the fan-beam data to fan-parallel-beam data and then using a modified parallel-beam BPF algorithm to obtain the reconstruction. This proposed algorithm retains the properties of the original fan-beam BPF algorithm in that it can reconstruct exact region of interest (ROI) images from truncated data and/or super-short-scan data. The major advantage of this algorithm is its improved noise properties because of the elimination of the spatially-variant weighting factor. In addition, the proposed algorithm is computationally more efficient