Artificial Intelligence in Head and Neck Imaging: A Glimpse into the Future.

Journal: Neuroimaging clinics of North America
Published Date:

Abstract

Artificial intelligence, specifically machine learning and deep learning, is a rapidly developing field in imaging sciences with the potential to improve the efficiency and effectiveness of radiologists. This review covers common technical terms and basic concepts in imaging artificial intelligence and briefly reviews the application of these techniques to general imaging as well as head and neck imaging. Artificial intelligence has the potential to contribute improvements to all areas of patient care, including image acquisition, processing, segmentation, automated detection of findings, integration of clinical information, quality improvement, and research. Numerous challenges remain, however, before widespread imaging clinical adoption and integration occur.

Authors

  • Kyle Werth
    Department of Radiology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Mailstop 4032, Kansas City, KS 66160, USA.
  • Luke Ledbetter
    Department of Radiology, David Geffen School of Medicine at UCLA, 757 Westwood Plaza, Suite 1621D, Los Angeles, CA 90095, USA. Electronic address: lledbetter@mednet.ucla.edu.