Deep learning for whole-body medical image generation.

Journal: European journal of nuclear medicine and molecular imaging
Published Date:

Abstract

BACKGROUND: Artificial intelligence (AI) algorithms based on deep convolutional networks have demonstrated remarkable success for image transformation tasks. State-of-the-art results have been achieved by generative adversarial networks (GANs) and training approaches which do not require paired data. Recently, these techniques have been applied in the medical field for cross-domain image translation.

Authors

  • Joshua Schaefferkoetter
    Siemens Medical Solutions USA, Inc., 810 Innovation Drive, Knoxville, TN, 37932, USA. joshua.schaefferkoetter@siemens.com.
  • Jianhua Yan
    State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China. Electronic address: yanjh@zju.edu.cn.
  • Sangkyu Moon
    Joint Department of Medical Imaging, Princess Margaret Cancer Centre, Mount Sinai Hospital and Women's College Hospital, University of Toronto, University Health Network, 610 University Ave, Toronto, Ontario, M5G 2M9, Canada.
  • Rosanna Chan
    Joint Department of Medical Imaging, Princess Margaret Cancer Centre, Mount Sinai Hospital and Women's College Hospital, University of Toronto, University Health Network, 610 University Ave, Toronto, Ontario, M5G 2M9, Canada.
  • Claudia Ortega
    Joint Department of Medical Imaging, Princess Margaret Cancer Centre, Mount Sinai Hospital and Women's College Hospital, University of Toronto, University Health Network, 610 University Ave, Toronto, Ontario, M5G 2M9, Canada.
  • Ur Metser
    Joint Department of Medical Imaging, Princess Margaret Cancer Centre, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, 610 University Ave, Ste 3-960, Toronto, ON M5G 2M9, Canada.
  • Alejandro Berlin
    Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
  • Patrick Veit-Haibach
    Toronto Joint Department Medical Imaging, University Health Network, Women's College Hospital, University of Toronto, Toronto, ON, Canada. Patrick.Veit-Haibach@uhn.ca.