Rapid whole-heart CMR with single volume super-resolution

Abstract Background Three-dimensional, whole heart, balanced steady state free precession (WH-bSSFP) sequences provide delineation of intra-cardiac and vascular anatomy. However, they have long acquisition times. Here, we propose significant speed-ups using a deep-learning single volume super-resolu...

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主要な著者:	Jennifer A. Steeden, Michael Quail, Alexander Gotschy, Kristian H. Mortensen, Andreas Hauptmann, Simon Arridge, Rodney Jones, Vivek Muthurangu
フォーマット:	Artigo
言語:	Inglês
出版事項:	Elsevier 2020-08-01
シリーズ:	Journal of Cardiovascular Magnetic Resonance
主題:	Super-resolution Whole-heart imaging Machine learning Rapid imaging Convolutional neural network
オンライン･アクセス:	http://link.springer.com/article/10.1186/s12968-020-00651-x
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