首页> Magnetic resonance in medicine> A probabilistic Bayesian approach to recover <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:semantics><mml:mrow><mml:msubsup><mml:mrow><mml:mi>R</mml:mi></mml:mrow><mml:mrow><mml:mn>2*</mml:mn></mml:mrow><mml:mrow /></mml:msubsup></mml:mrow><mml:annotation>$$ {R}_{2\ast } $$</mml:annotation></mml:semantics></mml:math> map and phase images for quantitative susceptibility mapping.

A probabilistic Bayesian approach to recover <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:semantics><mml:mrow><mml:msubsup><mml:mrow><mml:mi>R</mml:mi></mml:mrow><mml:mrow><mml:mn>2*</mml:mn></mml:mrow><mml:mrow /></mml:msubsup></mml:mrow><mml:annotation>$$ {R}_{2\ast } $$</mml:annotation></mml:semantics></mml:math> map and phase images for quantitative susceptibility mapping.

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第一作者： Shuai,Huang

第一单位： Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.

作者： Shuai,Huang ^[1] ; James J,Lah ^[2] ; Jason W,Allen ^[1] ; Deqiang,Qiu ^[1]

作者单位： Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA. ^[1] Department of Neurology, Emory University, Atlanta, Georgia, USA. ^[2]

关键词 R2*$$ {R}_{2\ast } $$ mapping approximate message passing compressive sensing parameter estimation quantitative susceptibility mapping undersampling

医学主题词算法(Algorithms);贝叶斯定理(Bayes Theorem);脑(Brain);图像处理, 计算机辅助(Image Processing, Computer-Assisted);磁共振成像(Magnetic Resonance Imaging);前瞻性研究(Prospective Studies);回顾性研究(Retrospective Studies)

DOI 10.1002/mrm.29303

PMID 35672899

发布时间 2023-11-07

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