Proton spot dose estimation based on positron activity distributions with neural network.

Journal: Medical physics
Published Date: Jul 10, 2024

Abstract

BACKGROUND: Positron emission tomography (PET) has been investigated for its ability to reconstruct proton-induced positron activity distributions in proton therapy. This technique holds potential for range verification in clinical practice. Recently, deep learning-based dose estimation from positron activity distributions shows promise for in vivo proton dose monitoring and guided proton therapy.

Authors

  • Ruilin Zhang
    School of Science, Jiangnan University, Wuxi, Jiangsu, 214122, China.
  • Dengyun Mu
    Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China.
  • Qiuhui Ma
    School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.
  • Lin Wan
    School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China.
  • Peng Xiao
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China. Electronic address: xiaopengaddis@hotmail.com.
  • Pengyuan Qi
    Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Gang Liu
    Department of Interventional Radiology, Qinghai Red Cross Hospital, Xining, Qinghai, China.
  • Sheng Zhang
    Department of Critical Care Medicine, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Taizhou, China.
  • Kunyu Yang
    Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Zhiyong Yang
  • Qingguo Xie
    Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China.

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