OBJECTIVES: To explore the impact of deep learning reconstruction (DLR) on image quality and machine learning-based coronary CT angiography (CTA)-derived fractional flow reserve (CT-FFR) values.
OBJECTIVES: Volumetric evaluation of coronary artery disease (CAD) allows better prediction of cardiac events. However, CAD segmentation is labor intensive. Our objective was to create an open-source deep learning (DL) model to segment coronary plaqu...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
May 5, 2022
Artificial intelligence may improve accuracy of myocardial perfusion imaging (MPI) but will likely be implemented as an aid to physician interpretation rather than an autonomous tool. Deep learning (DL) has high standalone diagnostic accuracy for obs...
Computational and mathematical methods in medicine
Apr 26, 2022
The coronary atherosclerotic heart disease is a common cardiovascular disease with high morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of the coronary atherosclerotic heart disease is of great significance. Th...
OBJECTIVES: Coronary computed tomography angiography (CCTA) has rapidly developed in the coronary artery disease (CAD) field. However, manual coronary artery tree segmentation and reconstruction are time-consuming and tedious. Deep learning algorithm...
Computer methods and programs in biomedicine
Mar 23, 2022
BACKGROUND AND OBJECTIVE: Automatic detection of stenosis on X-ray Coronary Angiography (XCA) images may help diagnose early coronary artery disease. Stenosis is manifested by a buildup of plaque in the arteries, decreasing the blood flow to the hear...
Currently, robotic-assisted coronary artery bypass grafting (RACABG) is a feasible choice for myocardial revascularization. Acceptable outcomes have been reported for RACABG with single target vessels; however, the long-term benefits of multivessel R...
OBJECTIVES: An automatic system utilizing both the advantages of the neural network and the radiomics was proposed for coronary plaque detection, classification, and stenosis grading.
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