Anatomy and Physiology of Artificial Intelligence in PET Imaging.

Journal: PET clinics
Published Date:

Abstract

Artificial intelligence (AI) has seen an explosion in interest within nuclear medicine. This interest is driven by the rapid progress and eye-catching achievements of machine learning algorithms. The growing foothold of AI in molecular imaging is exposing nuclear medicine personnel to new technology and terminology. Clinicians and researchers can be easily overwhelmed by numerous architectures and algorithms that have been published. This article dissects the backbone of most AI algorithms: the convolutional neural network. The algorithm training workflow and the key ingredients and operations of a convolutional neural network are described in detail. Finally, the ubiquitous U-Net is explained step-by-step.

Authors

  • Tyler J Bradshaw
    Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States of America.
  • Alan B McMillan
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705 USA, and also with the Department of Medical Physics, University of Wisconsin-Madison, Madison, WI 53705 USA.