首页> Magnetic resonance in medicine> QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.

QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.

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第一作者： Junghun,Cho

第一单位： Department of Radiology, Weill Cornell Medical College, New York, New York, USA.

作者： Junghun,Cho ^[1] ; Jinwei,Zhang ^[2] ; Pascal,Spincemaille ^[1] ; Hang,Zhang ^[2] ; Simon,Hubertus ^[1] ; Yan,Wen ^[2] ; Ramin,Jafari ^[2] ; Shun,Zhang ^[1] ; Thanh D,Nguyen ^[1] ; Alexey V,Dimov ^[1] ; Ajay,Gupta ^[1] ; Yi,Wang ^[3]

作者单位： Department of Radiology, Weill Cornell Medical College, New York, New York, USA. ^[1] Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA. ^[2] Department of Radiology, Weill Cornell Medical College, New York, New York, USA.;Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA. ^[3]

关键词 DL QQ QQ-NET QSM QSM+qBOLD Unet cerebral metabolic rate of oxygen deep learning oxygen extraction fraction qBOLD quantitative blood oxygenation level-dependent imaging quantitative susceptibility mapping

医学主题词脑(Brain);脑图(Brain Mapping);脑血管循环(Cerebrovascular Circulation);人类(Humans);磁共振成像(Magnetic Resonance Imaging);氧(Oxygen);氧耗量(Oxygen Consumption)

DOI 10.1002/mrm.29057

PMID 34719059

发布时间 2022-07-16

基金项目

K99 NS123229/NS/NINDS NIH HHS/United States S10 OD021782/OD/NIH HHS/United States R01 NS105144/NS/NINDS NIH HHS/United States R21 AG067466/AG/NIA NIH HHS/United States R01 NS095562/NS/NINDS NIH HHS/United States R01 NS090464/NS/NINDS NIH HHS/United States

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