Combining physics-based models with deep learning image synthesis and uncertainty in intraoperative cone-beam CT of the brain.

Abstract

Authors

• Xiaoxuan Zhang
  Department of Rheumatology and Immunology, Institute of Translational Medicine, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210002, China.
• Alejandro Sisniega
  Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
• Wojciech B Zbijewski
  Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
• Junghoon Lee
  Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
• Craig K Jones
  2Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore; and.
• Pengwei Wu
  Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
• Runze Han
  Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
• Ali Uneri
  Biomedical Engineering Department, Johns Hopkins University, Baltimore, MD, USA.
• Prasad Vagdargi
  Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.
• Patrick A Helm
  Medtronic Plc., Littleton, Massachusetts, USA.
• Mark Luciano
  Department of Neurosurgery, Johns Hopkins Hospital, Baltimore, Maryland, USA.
• William S Anderson
  Department of Neurosurgery, Johns Hopkins Hospital, Baltimore, Maryland, USA.
• Jeffrey H Siewerdsen
  Biomedical Engineering Department, Johns Hopkins University, Baltimore, MD, USA.

Keywords

External Resources