A deep learning-based peer review method for radiotherapy planning.

Journal: Medical physics
PMID: 39935240

Abstract

BACKGROUND: Quality control (QC) in radiotherapy planning is crucial for ensuring treatment efficacy and patient safety. Traditionally, QC relies on standard indicators and subjective assessments, which may lead to inconsistencies.

Authors

  • Pujun Zhou
  • Huikuan Gu
    Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.
  • Qinghe Peng
    State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China.
  • Dehua Kang
    State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China.
  • Jinhan Zhu
    a State Key Laboratory of Oncology in South China , Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center , Guangzhou , China.
  • Li Chen
    Department of Endocrinology and Metabolism, Qilu Hospital, Shandong University, Jinan, China.

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