A deep-learning-based dose verification tool utilizing fluence maps for a cobalt-60 compensator-based intensity-modulated radiation therapy system.

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作者： Kyuhak,Oh ^[1] ; Mary P,Gronberg ^[2] ; Tucker J,Netherton ^[2] ; Bishwambhar,Sengupta ^[2] ; Carlos E,Cardenas ^[1] ; Laurence E,Court ^[3] ; Eric C,Ford ^[2]

作者单位： Department of Radiation Oncology, University of Washington Medical Center, Seattle, WA 98195, USA. ^[1] Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. ^[2] Department of Radiation Oncology, University of Alabama, Birmingham, AL 35233, USA. ^[3]

关键词 Cobalt-60 compensator-based IMRT Deep-learning Dose prediction Fluence map

DOI 10.1016/j.phro.2023.100440

PMID 37342210

发布时间 2023-07-01

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Physics and imaging in radiation oncology

2023年26卷

100440页

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A deep-learning-based dose verification tool utilizing fluence maps for a cobalt-60 compensator-based intensity-modulated radiation therapy system.

Physics and imaging in radiation oncology

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Physics and imaging in radiation oncology

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A deep-learning-based dose verification tool utilizing fluence maps for a cobalt-60 compensator-based intensity-modulated radiation therapy system.

Physics and imaging in radiation oncology

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Physics and imaging in radiation oncology

相关期刊

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