Polar map-free 3D deep learning algorithm to predict obstructive coronary artery disease with myocardial perfusion CZT-SPECT
Journal
European journal of nuclear medicine and molecular imaging
Journal Volume
50
Journal Issue
2
Pages
376
Date Issued
2023-01-14
Author(s)
Lin, Shau-Syuan
Huang, Cheng-Wen
Chang, Yu-Hui
Wang, Shan-Ying
Abstract
Deep learning (DL) models have been shown to outperform total perfusion deficit (TPD) quantification in predicting obstructive coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, previously published methods have depended on polar maps, required manual correction, and normal database. In this study, we propose a polar map-free 3D DL algorithm to predict obstructive disease.
Subjects
Artificial intelligence; Cadmium-zinc-telluride; Coronary artery disease; Deep learning; Myocardial perfusion imaging
SDGs
Publisher
SPRINGER
Type
journal article