A modality conversion approach to MV-DRs and KV-DRRs registration using information bottlenecked conditional generative adversarial network.

Journal: Medical physics
Published Date:

Abstract

PURPOSE: As affordable equipment, electronic portal imaging devices (EPIDs) are wildly used in radiation therapy departments to verify patients' positions for accurate radiotherapy. However, these devices tend to produce visually ambiguous and low-contrast planar digital radiographs under megavoltage x ray (MV-DRs), which poses a tremendous challenge for clinicians to perform multimodal registration between the MV-DRs and the kilovoltage digital reconstructed radiographs (KV-DRRs) developed from the planning computed tomography. Furthermore, the existent of strong appearance variations also makes accurate registration beyond the reach of current automatic algorithms.

Authors

  • Cong Liu
    Department of Bioengineering, University of Illinois at Chicago, 851 S Morgan St, Chicago, IL, 60607, USA.
  • Zheming Lu
    School of Aeronautics and Astronautics, Zhejiang University, Hangzhou, 310058, China.
  • Longhua Ma
    Ningbo Institute of Technology, Zhejiang University, Ningbo, 315100, China.
  • Lang Wang
    Ningbo Institute of Technology, Zhejiang University, Ningbo, 315100, China.
  • Xiance Jin
    Department of Radiation and Medical Oncology, The 1st Affiliated Hospital of Wenzhou Medical University, No.2 Fuxue Lane, Wenzhou, 325000, People's Republic of China.
  • Wen Si
    Internet of Things College, Shanghai Business School, Shanghai, 201400, China.