Computed Tomography Perfusion-Based Prediction of Core Infarct and Tissue at Risk: Can Artificial Intelligence Help Reduce Radiation Exposure?

Journal: Stroke
Published Date: Dec 1, 2021

Abstract

BACKGROUND AND PURPOSE: We explored the feasibility of automated, arterial input function independent, vendor neutral prediction of core infarct, and penumbral tissue using complete and partial computed tomographic perfusion data sets through neural networks.

Authors

  • Girish Bathla
    Mayo Clinic Rochester, Minnesota, USA.
  • Yanan Liu
    College of Environmental Science and Engineering, Donghua University, 2999 North Renmin Road, Shanghai 201620, China.
  • Honghai Zhang
    Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA 52242, USA.
  • Milan Sonka
    Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, 52242, United States; Department of Ophthalmology and Visual Sciences, The University of Iowa, Iowa City, IA, 52242, United States.
  • Colin Derdeyn
    Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City (G.B., C.D.).

Keywords

External Resources

Popular Topics
Recent Journals