Xingfeng Shao, M Dylan Tisdall, Danny Jj Wang, Andre Jan Willem van der Kouwe
{"title":"Prospective motion correction for 3D GRASE pCASL with volumetric navigators.","authors":"Xingfeng Shao, M Dylan Tisdall, Danny Jj Wang, Andre Jan Willem van der Kouwe","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>We propose a prospective motion correction approach for background suppressed (BS) segmented 3D GRASE pCASL using volumetric EPI-based navigators (vNavs), which causes minimal contrast change and no extra time. vNavs reduced motion artifacts effectively and increased temporal signal-to-noise ratio (t-SNR). Principle component analysis (PCA) is able to further reduce residual motion artifacts and restore the details of gyral structure in perfusion weighted images..</p>","PeriodicalId":74549,"journal":{"name":"Proceedings of the International Society for Magnetic Resonance in Medicine ... Scientific Meeting and Exhibition. International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition","volume":"25 ","pages":"0680"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891141/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Society for Magnetic Resonance in Medicine ... Scientific Meeting and Exhibition. International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We propose a prospective motion correction approach for background suppressed (BS) segmented 3D GRASE pCASL using volumetric EPI-based navigators (vNavs), which causes minimal contrast change and no extra time. vNavs reduced motion artifacts effectively and increased temporal signal-to-noise ratio (t-SNR). Principle component analysis (PCA) is able to further reduce residual motion artifacts and restore the details of gyral structure in perfusion weighted images..
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