{"title":"突破了磁共振扩散张量成像的采集时限","authors":"E. Hsu","doi":"10.1109/ACSSC.2008.5074652","DOIUrl":null,"url":null,"abstract":"Magnetic resonance diffusion tensor imaging is a powerful tool and increasingly used to characterize the microstructure of ordered tissues such as the brain white matter and myocardium. However, its practical applications have been hampered by low SNR and long scan time. The current paper describes techniques combining reduced encoding imaging and constrained reconstruction that are greatly promising for breaking through these limitations.","PeriodicalId":416114,"journal":{"name":"2008 42nd Asilomar Conference on Signals, Systems and Computers","volume":"152 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pushing the acquisition time limit of magnetic resonance diffusion tensor imaging\",\"authors\":\"E. Hsu\",\"doi\":\"10.1109/ACSSC.2008.5074652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Magnetic resonance diffusion tensor imaging is a powerful tool and increasingly used to characterize the microstructure of ordered tissues such as the brain white matter and myocardium. However, its practical applications have been hampered by low SNR and long scan time. The current paper describes techniques combining reduced encoding imaging and constrained reconstruction that are greatly promising for breaking through these limitations.\",\"PeriodicalId\":416114,\"journal\":{\"name\":\"2008 42nd Asilomar Conference on Signals, Systems and Computers\",\"volume\":\"152 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 42nd Asilomar Conference on Signals, Systems and Computers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.2008.5074652\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 42nd Asilomar Conference on Signals, Systems and Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2008.5074652","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pushing the acquisition time limit of magnetic resonance diffusion tensor imaging
Magnetic resonance diffusion tensor imaging is a powerful tool and increasingly used to characterize the microstructure of ordered tissues such as the brain white matter and myocardium. However, its practical applications have been hampered by low SNR and long scan time. The current paper describes techniques combining reduced encoding imaging and constrained reconstruction that are greatly promising for breaking through these limitations.