Deep learning prediction of quantitative coronary angiography values using myocardial perfusion images with a CZT camera.

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

PMID: 35610536

PURPOSE: Evaluate the prediction of quantitative coronary angiography (QCA) values from MPI, by means of deep learning.

Ida Arvidsson

Centre for Mathematical Sciences, Lund University, Lund, Sweden.
Anette Davidsson

Department of Clinical Physiology, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Niels Christian Overgaard

Centre for Mathematical Sciences, Lund University, Lund, Sweden.
Christos Pagonis

Department of Cardiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Kalle Åström

Centre for Mathematical Sciences, Lund University, Lund, Sweden.
Elin Good

Division of Cardiovascular Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Jeronimo Frias-Rose

Department of Pathology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Anders Heyden

Centre for Mathematical Sciences, Lund University, Lund, Sweden.
Miguel Ochoa-Figueroa

Department of Clinical Physiology, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.

Cadmium Coronary Angiography Coronary Artery Disease Coronary Stenosis Deep Learning Female Humans Male Myocardial Perfusion Imaging Perfusion Tellurium Tomography, Emission-Computed, Single-Photon

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