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A single neural network for cone-beam computed tomography-based radiotherapy of head-and-neck, lung and breast cancer.

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第一作者： Matteo,Maspero

第一单位： Department of radiotherapy, division of imaging & oncology, University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, The Netherlands.;Computational imaging group for MR diagnostics & therapy, center for image sciences, University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, The Netherlands.

作者： Matteo,Maspero ^[1] ; Antonetta C,Houweling ^[2] ; Mark H F,Savenije ^[1] ; Tristan C F,van Heijst ^[2] ; Joost J C,Verhoeff ^[2] ; Alexis N T J,Kotte ^[2] ; Cornelis A T,van den Berg ^[1]

作者单位： Department of radiotherapy, division of imaging & oncology, University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, The Netherlands.;Computational imaging group for MR diagnostics & therapy, center for image sciences, University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, The Netherlands. ^[1] Department of radiotherapy, division of imaging & oncology, University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, The Netherlands. ^[2]

关键词 Adaptive radiotherapy Artificial intelligence CBCT Deep learning Dose calculation Image-guided radiotherapy Image-to-image translation Machine learning

DOI 10.1016/j.phro.2020.04.002

PMID 33458310

发布时间 2021-01-19

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Physics and imaging in radiation oncology

2020年14卷

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Physics and imaging in radiation oncology

2020年14卷

24-31页

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A single neural network for cone-beam computed tomography-based radiotherapy of head-and-neck, lung and breast cancer.

Physics and imaging in radiation oncology

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A single neural network for cone-beam computed tomography-based radiotherapy of head-and-neck, lung and breast cancer.

Physics and imaging in radiation oncology

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Physics and imaging in radiation oncology

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