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Comparative evaluation of a prototype deep learning algorithm for autosegmentation of normal tissues in head and neck radiotherapy.

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第一作者： Jihye,Koo

第一单位： Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA; Department of Physics, University of South Florida, FL, USA. Electronic address: jihye.koo@moffitt.org.

作者： Jihye,Koo ^[1] ; Jimmy J,Caudell ^[2] ; Kujtim,Latifi ^[3] ; Petr,Jordan ^[4] ; Sangyu,Shen ^[5] ; Philip M,Adamson ^[6] ; Eduardo G,Moros ^[7] ; Vladimir,Feygelman ^[8]

作者单位： Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA; Department of Physics, University of South Florida, FL, USA. Electronic address: jihye.koo@moffitt.org. ^[1] Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA. Electronic address: jimmy.caudell@moffitt.org. ^[2] Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA. Electronic address: kujtim.latifi@moffitt.org. ^[3] Varian Medical Systems, Palo Alto, CA, USA. Electronic address: petr.jordan@gmail.com. ^[4] Varian Medical Systems, Palo Alto, CA, USA. Electronic address: sangyu.shen@varian.com. ^[5] Varian Medical Systems, Palo Alto, CA, USA. Electronic address: padamson@stanford.edu. ^[6] Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA. Electronic address: eduardo.moros@moffitt.org. ^[7] Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA. Electronic address: vladimir.feygelman@moffitt.org. ^[8]

关键词 Deep learning autosegmentation Head and neck organs at risk Radiotherapy planning

医学主题词算法(Algorithms);头颈部肿瘤(Head and Neck Neoplasms);人类(Humans);危及器官(Organs at Risk);放射治疗计划, 计算机辅助(Radiotherapy Planning, Computer-Assisted);结果可重复性(Reproducibility of Results)

DOI 10.1016/j.radonc.2022.06.024

PMID 35817322

发布时间 2022-10-04

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