Objective Task-Based Evaluation of Artificial Intelligence-Based Medical Imaging Methods:: Framework, Strategies, and Role of the Physician.

Journal: PET clinics
Published Date: Oct 1, 2021

Abstract

Artificial intelligence-based methods are showing promise in medical imaging applications. There is substantial interest in clinical translation of these methods, requiring that they be evaluated rigorously. We lay out a framework for objective task-based evaluation of artificial intelligence methods. We provide a list of available tools to conduct this evaluation. We outline the important role of physicians in conducting these evaluation studies. The examples in this article are proposed in the context of PET scans with a focus on evaluating neural network-based methods. However, the framework is also applicable to evaluate other medical imaging modalities and other types of artificial intelligence methods.

Authors

  • Abhinav K Jha
    Department of Biomedical Engineering and Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States of America.
  • Kyle J Myers
    Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration (FDA), Silver Spring, MD, USA.
  • Nancy A Obuchowski
    Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.
  • Ziping Liu
    Department of Biomedical Engineering, Washington University in St. Louis, 1 Brookings Drive, St Louis, MO 63130, USA.
  • Md Ashequr Rahman
    Department of Biomedical Engineering, Washington University in St. Louis, 1 Brookings Drive, St Louis, MO 63130, USA.
  • Babak Saboury
    IBM Research, Almaden, San Jose, California.
  • Arman Rahmim
  • Barry A Siegel
    Division of Nuclear Medicine, Mallinckrodt Institute of Radiology, Alvin J. Siteman Cancer Center, Washington University School of Medicine, 510 S Kingshighway Boulevard #956, St Louis, MO 63110, USA.

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