Geometric and dosimetric evaluation of deep learning-based organs at risk auto-segmentation for rectal cancer
RADIOBIOLOGY AND RADIOMEDICINE|更新时间:2025-03-01
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Geometric and dosimetric evaluation of deep learning-based organs at risk auto-segmentation for rectal cancer
“A study by Fudan University Affiliated Cancer Hospital shows that deep learning automatic delineation of endangered organs is highly similar to manual delineation by doctors, with little impact on dose distribution and potential for clinical application.”
Journal of Radiation Research and Radiation ProcessingVol. 40, Issue 2, Pages: 60-68(2022)
GUO Hongbo (male) was born in February 1993, and obtained his master's degree from University of Science and Technology of China in 2019. Now he works at the Department of Radiation Oncology of Fudan University Shanghai Cancer as a medical physicist, engaging in medical physics of radiation therapy
HU Weigang, professor, E-mail: jackhuwg@gmail.com
基金信息:
Shanghai Committee of Science and Technology Fund(19DZ1930902)
GUO Hongbo,WANG Jiazhou,YANG Cui,et al.Geometric and dosimetric evaluation of deep learning-based organs at risk auto-segmentation for rectal cancer[J].Journal of Radiation Research and Radiation Processing,2022,40(02):60-68.
GUO Hongbo,WANG Jiazhou,YANG Cui,et al.Geometric and dosimetric evaluation of deep learning-based organs at risk auto-segmentation for rectal cancer[J].Journal of Radiation Research and Radiation Processing,2022,40(02):60-68. DOI: 10.11889/j.1000-3436.2021-0208.
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Related Institution
Cancer Clinical Medical Center, Radiation Oncology Center, the First People Hospital of Zunyi/ the Third Affiliated Hospital of Zunyi Medical University
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