Multiresolution residual deep neural network for improving pelvic CBCT image quality.

Journal: Medical physics
Published Date: Jan 27, 2022

Abstract

PURPOSE: Cone-beam computed tomography (CBCT) is frequently used for accurate image-guided radiation therapy. However, the poor CBCT image quality prevents its further clinical use. Thus, it is important to improve the HU accuracy and structure preservation of CBCT images.

Authors

  • Wangjiang Wu
    Department of Radiation Oncology, Peking University Third Hospital, Beijing, China.
  • Junda Qu
    School of Biomedical Engineering, Capital Medical University, Beijing, China.
  • Jing Cai
    Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.
  • Ruijie Yang
    Department of Radiation Oncology, Peking University Third Hospital, Beijing, China. Electronic address: ruijyang@yahoo.com.

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