Interpretation of SPECT wall motion with deep learning.

Journal: Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology

Published Date: May 7, 2024

OBJECTIVES: We sought to develop a novel deep learning (DL) workflow to interpret single-photon emission computed tomography (SPECT) wall motion.

Yangmei Zhang

School of Biomedical Engineering, Southern Medical University, Guangzhou, China; Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China.
Emma Bos

Department of Physics, Engineering Physics & Astronomy, Queen's University, Canada.
Owen Clarkin

Department of Medicine (Cardiology), University of Ottawa Heart Institute, Ottawa, Ontario, Canada.
Tyler Wilson

Department of Applied Science in Computer Engineering, Queen's University, Canada.
Gary R Small

Department of Medicine, Division of Cardiology, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON K1Y 4W7, Canada.
R Glenn Wells

Department of Medicine (Cardiology), University of Ottawa Heart Institute, Canada.
Lijun Lu

School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
Benjamin J W Chow

Department of Medicine, Division of Cardiology, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON K1Y 4W7, Canada.

Aged Coronary Artery Disease Deep Learning Echocardiography Electrocardiography Female Humans Male Middle Aged Reproducibility of Results ROC Curve Tomography, Emission-Computed, Single-Photon

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