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Deep learning-based prediction of intra-cardiac blood flow in long-axis cine magnetic resonance imaging.

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Title: Deep learning-based prediction of intra-cardiac blood flow in long-axis cine magnetic resonance imaging.
Authors: Sun X; Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands., Cheng LH; Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands., Plein S; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK., Garg P; Norwich Medical School, University of East Anglia, Norwich, UK.; Norfolk and Norwich University Hospital Foundation Trust, Norwich, UK., Moghari MH; Department of Radiology, Children's Hospital Colorado, and School of Medicine, The University of Colorado, Boulder, CO, USA., van der Geest RJ; Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands. R.J.van_der_Geest@lumc.nl.
Source: The international journal of cardiovascular imaging [Int J Cardiovasc Imaging] 2023 May; Vol. 39 (5), pp. 1045-1053. Date of Electronic Publication: 2023 Feb 10.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: United States NLM ID: 100969716 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1875-8312 (Electronic) Linking ISSN: 15695794 NLM ISO Abbreviation: Int J Cardiovasc Imaging Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Deep learning-based prediction of intra-cardiac blood flow in long-axis cine magnetic resonance imaging.
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  Data: <searchLink fieldCode="AU" term="%22Sun+X%22">Sun X</searchLink>; Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Cheng+LH%22">Cheng LH</searchLink>; Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Plein+S%22">Plein S</searchLink>; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.<br /><searchLink fieldCode="AU" term="%22Garg+P%22">Garg P</searchLink>; Norwich Medical School, University of East Anglia, Norwich, UK.; Norfolk and Norwich University Hospital Foundation Trust, Norwich, UK.<br /><searchLink fieldCode="AU" term="%22Moghari+MH%22">Moghari MH</searchLink>; Department of Radiology, Children's Hospital Colorado, and School of Medicine, The University of Colorado, Boulder, CO, USA.<br /><searchLink fieldCode="AU" term="%22van+der+Geest+RJ%22">van der Geest RJ</searchLink>; Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands. R.J.van_der_Geest@lumc.nl.
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  Data: <searchLink fieldCode="JN" term="%22100969716%22">The international journal of cardiovascular imaging</searchLink> [Int J Cardiovasc Imaging] 2023 May; Vol. 39 (5), pp. 1045-1053. <i>Date of Electronic Publication: </i>2023 Feb 10.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer%22">Springer </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>100969716 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1875-8312 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2215695794%22">15695794 </searchLink><i>NLM ISO Abbreviation: </i>Int J Cardiovasc Imaging <i>Subsets: </i>MEDLINE
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        Value: 10.1007/s10554-023-02804-2
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              Text: 2023 May
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