Artificial Intelligence for Brain Molecular Imaging.

Journal: PET clinics
Published Date:

Abstract

AI has been applied to brain molecular imaging for over 30 years. The past two decades, have seen explosive progress. AI applications span from operations processes such as attenuation correction and image generation, to disease diagnosis and prediction. As sophistication in AI software platforms increases, and the availability of large imaging data repositories become common, future studies will incorporate more multidimensional datasets and information that may truly reach "superhuman" levels in the field of brain imaging. However, even with a growing level of complexity, these advanced networks will still require human supervision for appropriate application and interpretation in medical practice.

Authors

  • Donna J Cross
    Department of Radiology and Imaging Sciences, University of Utah, 30 North 1900 East #1A71, Salt Lake City, UT 84132-2140, USA. Electronic address: d.cross@utah.edu.
  • Seisaku Komori
    Future Design Lab, New Concept Design, Global Strategic Challenge Center, Hamamatsu Photonics K.K. 5000, Hirakuchi, Hamakita-ku, Hamamatsu-City, 434-8601 Japan.
  • Satoshi Minoshima
    Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah.