A Review on Artificial Intelligence – Assisted CCTA Imaging for CAD Diagnosis

According to the statistics committee of the American Heart Association, Coronary Artery Disease (CAD) or myocardial ischemia is one of the most common Cardiovascular Diseases (CVD) that has high morbidity and mortality worldwide. Though Invasive Coronary Angiography (ICA) is recognized as the gold standard for the diagnosis of stenosis-related CAD owing to its ability to identify and classify stenoses precisely, it has severe complications and side effects. As a result, Image segmentation evaluation parameters and Automatic diagnosis have all benefited by using AI in non invasive technology known as CCTA (Coronary Computed Tomography Angiography). The purpose of this mini-review study is to understand the development of AI-assisted approaches for image processing, feature extraction, plaque recognition, and characterization in CCTA. Furthermore, the benefits, drawbacks, and potential applications of AI in diagnostic testing of atherosclerotic lesions are reviewed.