{"title":"具有阈值的广义逆重构算法","authors":"Huaxiang Wang, Yongbo He, Chao Wang","doi":"10.1109/IMTC.2004.1351100","DOIUrl":null,"url":null,"abstract":"In this paper, a method called the generalized inverse image reconstruction algorithm with threshold based on the Geselowitz sensitivity theorem is proposed, and the selection way of the regularization parameter is also presented. Both theoretical and experimental results show that this proposed algorithm can provide images superior to those obtained with filtered back-projection (FBP) and the sensitivity coefficient algorithm.","PeriodicalId":386903,"journal":{"name":"Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generalized inverse reconstruction algorithm with threshold\",\"authors\":\"Huaxiang Wang, Yongbo He, Chao Wang\",\"doi\":\"10.1109/IMTC.2004.1351100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a method called the generalized inverse image reconstruction algorithm with threshold based on the Geselowitz sensitivity theorem is proposed, and the selection way of the regularization parameter is also presented. Both theoretical and experimental results show that this proposed algorithm can provide images superior to those obtained with filtered back-projection (FBP) and the sensitivity coefficient algorithm.\",\"PeriodicalId\":386903,\"journal\":{\"name\":\"Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510)\",\"volume\":\"212 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMTC.2004.1351100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMTC.2004.1351100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generalized inverse reconstruction algorithm with threshold
In this paper, a method called the generalized inverse image reconstruction algorithm with threshold based on the Geselowitz sensitivity theorem is proposed, and the selection way of the regularization parameter is also presented. Both theoretical and experimental results show that this proposed algorithm can provide images superior to those obtained with filtered back-projection (FBP) and the sensitivity coefficient algorithm.