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Physics-based reconstruction methods for magnetic resonance imaging.
Wang, Xiaoqing; Tan, Zhengguo; Scholand, Nick; Roeloffs, Volkert; Uecker, Martin.
Afiliação
  • Wang X; Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany.
  • Tan Z; Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany.
  • Scholand N; Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany.
  • Roeloffs V; Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany.
  • Uecker M; Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany.
Philos Trans A Math Phys Eng Sci ; 379(2200): 20200196, 2021 Jun 28.
Article em En | MEDLINE | ID: mdl-33966457
ABSTRACT
Conventional magnetic resonance imaging (MRI) is hampered by long scan times and only qualitative image contrasts that prohibit a direct comparison between different systems. To address these limitations, model-based reconstructions explicitly model the physical laws that govern the MRI signal generation. By formulating image reconstruction as an inverse problem, quantitative maps of the underlying physical parameters can then be extracted directly from efficiently acquired k-space signals without intermediate image reconstruction-addressing both shortcomings of conventional MRI at the same time. This review will discuss basic concepts of model-based reconstructions and report on our experience in developing several model-based methods over the last decade using selected examples that are provided complete with data and code. This article is part of the theme issue 'Synergistic tomographic image reconstruction part 1'.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador Tipo de estudo: Qualitative_research Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Interpretação de Imagem Assistida por Computador Tipo de estudo: Qualitative_research Limite: Adult / Female / Humans / Male Idioma: En Ano de publicação: 2021 Tipo de documento: Article