Approaching automated applicator digitization from a new angle: Using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy-论文-万方医学网

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Approaching automated applicator digitization from a new angle: Using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy

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第一作者： Weishaupt, Luca Leon

作者： Weishaupt, Luca Leon ^[1] ; Sayed, Hisham Kamal ^[2] ; Mao, Ximeng ^[3] ; Choo, Richard ; Stish, Bradley J. ; Enger, Shirin A. ; Deufel, Christopher

作者单位： Mayo Clinic,Mayo Clin ^[1] Mila Quebec AI Inst ^[2] Med Phys Unit,McGill Univ ^[3]

关键词 Deep learning Applicator digitization Brachytherapy Prostate Segmentation CATHETER DISPLACEMENT UNCERTAINTIES

发布时间 2022-11-17

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Approaching automated applicator digitization from a new angle: Using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy

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Approaching automated applicator digitization from a new angle: Using sagittal images to improve deep learning accuracy and robustness in high-dose-rate prostate brachytherapy

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