Nucl Med Mol Imaging.  2023 Apr;57(2):51-60. 10.1007/s13139-021-00733-3.

Preparing for the Artificial Intelligence Revolution in Nuclear Cardiology

Affiliations
  • 1Department of Radiology and Imaging Sciences, Emory University School of Medicine, 101 Woodruff Circle, Room 1203, GA 30322 Atlanta, USA

Abstract

A major opportunity in nuclear cardiology is the many significant artificial intelligence (AI) applications that have recently been reported. These developments include using deep learning (DL) for reducing the needed injected dose and acquisition time in perfusion acquisitions also due to DL improvements in image reconstruction and filtering, SPECT attenuation correction using DL without need for transmission images, DL and machine learning (ML) use for feature extraction to define myocardial left ventricular (LV) borders for functional measurements and improved detection of the LV valve plane and AI, ML, and DL implementations for MPI diagnosis, prognosis, and structured reporting. Although some have, most of these applications have yet to make it to widespread commercial distribution due to the recency of their developments, most reported in 2020. We must be prepared both technically and socio-economically to fully benefit from these and a tsunami of other AI applications that are coming.

Keyword

Nuclear cardiology; Absolute myocardial blood flow; Myocardial flow reserve; Artificial intelligence; Machine learning; Deep learning
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