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Combining deep learning and 3D contrast source inversion in MR-based electrical properties tomography.

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Title: Combining deep learning and 3D contrast source inversion in MR-based electrical properties tomography.
Authors: Leijsen R; Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands., van den Berg C; Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, Utrecht University, Utrecht, The Netherlands., Webb A; Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands., Remis R; Circuits and Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands., Mandija S; Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, Utrecht University, Utrecht, The Netherlands.
Source: NMR in biomedicine [NMR Biomed] 2022 Apr; Vol. 35 (4), pp. e4211. Date of Electronic Publication: 2019 Dec 16.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Wiley Country of Publication: England NLM ID: 8915233 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1099-1492 (Electronic) Linking ISSN: 09523480 NLM ISO Abbreviation: NMR Biomed Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Leijsen+R%22">Leijsen R</searchLink>; Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands.<br /><searchLink fieldCode="AU" term="%22van+den+Berg+C%22">van den Berg C</searchLink>; Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, Utrecht University, Utrecht, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Webb+A%22">Webb A</searchLink>; Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Remis+R%22">Remis R</searchLink>; Circuits and Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Mandija+S%22">Mandija S</searchLink>; Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, Utrecht University, Utrecht, The Netherlands.
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  Data: <searchLink fieldCode="JN" term="%228915233%22">NMR in biomedicine</searchLink> [NMR Biomed] 2022 Apr; Vol. 35 (4), pp. e4211. <i>Date of Electronic Publication: </i>2019 Dec 16.
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        Value: 10.1002/nbm.4211
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      – TitleFull: Combining deep learning and 3D contrast source inversion in MR-based electrical properties tomography.
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              Text: 2022 Apr
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