QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.

Abstract

Authors

• Junghun Cho
  Department of Biomedical Engineering, Cornell University, Ithaca, New York.
• Jinwei Zhang
  Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
• Pascal Spincemaille
  Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
• Hang Zhang
  Department of Cardiology, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
• Simon Hubertus
  Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
• Yan Wen
• Ramin Jafari
  Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
• Shun Zhang
  Department of Radiology, Weill Cornell Medical College, New York, New York.
• Thanh D Nguyen
  Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
• Alexey V Dimov
  Department of Radiology, Weill Cornell Medical College, New York, New York, USA.
• Ajay Gupta
• Yi Wang
  Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.

Keywords

External Resources