Head and neck synthetic CT generated from ultra-low-dose cone-beam CT following Image Gently Protocol using deep neural network.

Journal: Medical physics
Published Date: Mar 14, 2022

Abstract

PURPOSE: Image guidance is used to improve the accuracy of radiation therapy delivery but results in increased dose to patients. This is of particular concern in children who need be treated per Pediatric Image Gently Protocols due to long-term risks from radiation exposure. The purpose of this study is to design a deep neural network architecture and loss function for improving soft-tissue contrast and preserving small anatomical features in ultra-low-dose cone-beam CTs (CBCT) of head and neck cancer (HNC) imaging.

Authors

  • Nimu Yuan
    Department of Biomedical Engineering, University of California, Davis, CA, United States.
  • Shyam Rao
    Department of Radiation Oncology, University of California Davis Medical Center, Sacramento, CA, United States.
  • Quan Chen
    Management School, Zhongshan Institute, University of Electronic Science and Technology of China, Guangdong, 528402, China.
  • Levent Sensoy
    Department of Radiation Oncology, University of California Davis Medical Center, Sacramento, CA, United States.
  • Jinyi Qi
    Department of Biomedical Engineering, University of California, Davis, CA, United States.
  • Yi Rong
    Department of Radiation Oncology, University of California Davis Medical Center, Sacramento, CA, United States.

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