{"title":"约束ARMA磁共振成像方法","authors":"M.R. Smith","doi":"10.1109/SSAP.1992.246889","DOIUrl":null,"url":null,"abstract":"Quantitative measurement on medical phantoms has shown that the transient error reconstruction approach (TERA), successfully reintroduces 40% to 50% of truncated energy. This indicates a considerable increase in resolution and reduction in image artifacts. The algorithm is not as successful on normal medical data. This paper suggests an approach to constrain the modeling algorithm to include a priori information and improve the modeling. Preliminary results are presented for a constraint that introduces additional edge information into the TERA algorithm.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Constrained ARMA method for magnetic resonance imaging\",\"authors\":\"M.R. Smith\",\"doi\":\"10.1109/SSAP.1992.246889\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantitative measurement on medical phantoms has shown that the transient error reconstruction approach (TERA), successfully reintroduces 40% to 50% of truncated energy. This indicates a considerable increase in resolution and reduction in image artifacts. The algorithm is not as successful on normal medical data. This paper suggests an approach to constrain the modeling algorithm to include a priori information and improve the modeling. Preliminary results are presented for a constraint that introduces additional edge information into the TERA algorithm.<<ETX>>\",\"PeriodicalId\":309407,\"journal\":{\"name\":\"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSAP.1992.246889\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSAP.1992.246889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Constrained ARMA method for magnetic resonance imaging
Quantitative measurement on medical phantoms has shown that the transient error reconstruction approach (TERA), successfully reintroduces 40% to 50% of truncated energy. This indicates a considerable increase in resolution and reduction in image artifacts. The algorithm is not as successful on normal medical data. This paper suggests an approach to constrain the modeling algorithm to include a priori information and improve the modeling. Preliminary results are presented for a constraint that introduces additional edge information into the TERA algorithm.<>
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