OBJECTIVES: This study aimed to assess the impact of super-resolution deep learning reconstruction (SR-DLR) on coronary CT angiography (CCTA) image quality and blooming artifacts from coronary artery stents in comparison to conventional methods, incl...
OBJECTIVES: In 2018, CMS established reimbursement for the first Medicare-covered artificial intelligence (AI)-enabled clinical software: CT fractional flow reserve (FFRCT) to assist in the diagnosis of coronary artery disease. This study quantified ...
OBJECTIVES: Coronary angiography (CAG)-derived physiology methods have been developed in an attempt to simplify and increase the usage of coronary physiology, based mostly on dynamic fluid computational algorithms. We aimed to develop a different app...
Coronary CT angiography is increasingly used for cardiac diagnosis. Dose modulation techniques can reduce radiation dose, but resulting functional images are noisy and challenging for functional analysis. This retrospective study describes and evalua...
Mathematical biosciences and engineering : MBE
Feb 23, 2024
With the widespread adoption of electronic health records, the amount of stored medical data has been increasing. Clinical data, often in the form of semi-structured or unstructured electronic medical records (EMRs), contains rich patient information...
Therapeutic advances in cardiovascular disease
Jan 1, 2024
Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality of cardiac structures and vasculature considered comparable to invasive coronary angiography for the evaluation of coronary artery disease (CAD) in several major cardio...
OBJECTIVE: Challenging HR conditions, such as elevated Heart Rate (HR) and Heart Rate Variability (HRV), are major contributors to motion artifacts in Coronary Computed Tomography Angiography (CCTA). This study aims to assess the impact of a deep lea...
UNLABELLED: Background CT is helpful in guiding the revascularization of chronic total occlusion (CTO), but manual prediction scores of percutaneous coronary intervention (PCI) success have challenges. Deep learning (DL) is expected to predict succes...
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