The feasibility study on the generalization of deep learning dose prediction model for volumetric modulated arc therapy of cervical cancer.

Journal: Journal of applied clinical medical physics
PMID: 35262273

Abstract

PURPOSE: To develop a 3D-Unet dose prediction model to predict the three-dimensional dose distribution of volumetric modulated arc therapy (VMAT) for cervical cancer and test the dose prediction performance of the model in endometrial cancer to explore the feasibility of model generalization.

Authors

  • Zhang Qilin
    Department of Radiation Oncology, Peking University Third Hospital, Beijing, China.
  • Bao Peng
    Center for Data Science, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
  • Qu Ang
    Department of Radiation Oncology, Peking University Third Hospital, Beijing, China.
  • Jiang Weijuan
    Department of Radiation Oncology, Peking University Third Hospital, Beijing, China.
  • Jiang Ping
    Department of Radiation Oncology, Peking University Third Hospital, Beijing, China.
  • Zhuang Hongqing
    Department of Radiation Oncology, Peking University Third Hospital, Beijing, China.
  • Dong Bin
    Beijing International Center for Mathematical Research, Peking University, Beijing, China.
  • Yang Ruijie
    Department of Radiation Oncology, Peking University Third Hospital, Beijing, China.

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