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Coronary Angiography

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Evaluation of a deep learning model on coronary CT angiography for automatic stenosis detection.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to evaluate a deep-learning model (DLM) for classifying coronary arteries on coronary computed tomography -angiography (CCTA) using the Coronary Artery Disease-Reporting and Data System (CAD-RADS).

Automatic construction of coronary artery tree structure based on vessel blood flow tracking.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
We sought to propose an innovative vessel blood flow tracking (VBFT) method to extract coronary artery tree (CAT) and to assess the effectiveness of this VBFT versus the single-frame method. Construction of a CAT from a segmented artery is the basis ...

High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.

European radiology
OBJECTIVES: To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26 kg/m,...

Vessel segmentation for X-ray coronary angiography using ensemble methods with deep learning and filter-based features.

BMC medical imaging
BACKGROUND: Automated segmentation of coronary arteries is a crucial step for computer-aided coronary artery disease (CAD) diagnosis and treatment planning. Correct delineation of the coronary artery is challenging in X-ray coronary angiography (XCA)...

Automated segmentation of metal stent and bioresorbable vascular scaffold in intravascular optical coherence tomography images using deep learning architectures.

Physics in medicine and biology
Percutaneous coronary intervention (PCI) with stent placement is a treatment effective for coronary artery diseases. Intravascular optical coherence tomography (OCT) with high resolution is used clinically to visualize stent deployment and restenosis...

Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review.

Circulation. Cardiovascular imaging
The risk of coronary heart disease (CHD) clinical manifestations and patient management is estimated according to risk scores accounting multifactorial risk factors, thus failing to cover the individual cardiovascular risk. Technological improvements...

Reconnection of fragmented parts of coronary arteries using local geometric features in X-ray angiography images.

Computers in biology and medicine
UNLABELLED: The segmentation of coronary arteries in X-ray images is essential for image-based guiding procedures and the diagnosis of cardiovascular disease. However, owing to the complex and thin structures of the coronary arteries, it is challengi...

Deep Learning-Based Approach to Automatically Assess Coronary Distensibility Following Kawasaki Disease.

Pediatric cardiology
Kawasaki disease is an acute vasculitis affecting children, which can lead to coronary artery (CA) aneurysms. Optical coherence tomography (OCT) has identified CA wall damage in KD patients, but it is unclear if these findings correlate with any dist...