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Coronary Angiography

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Robotically performed diagnostic coronary angiography.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
OBJECTIVE: This study was performed to investigate the efficacy and safety of robotic diagnostic coronary angiography.

Development of deep learning segmentation models for coronary X-ray angiography: Quality assessment by a new global segmentation score and comparison with human performance.

Revista portuguesa de cardiologia : orgao oficial da Sociedade Portuguesa de Cardiologia = Portuguese journal of cardiology : an official journal of the Portuguese Society of Cardiology
INTRODUCTION AND OBJECTIVES: Although automatic artificial intelligence (AI) coronary angiography (CAG) segmentation is arguably the first step toward future clinical application, it is underexplored. We aimed to (1) develop AI models for CAG segment...

Optical flow estimation of coronary angiography sequences based on semi-supervised learning.

Computers in biology and medicine
Optical flow is widely used in medical image processing, such as image registration, segmentation, 3D reconstruction, and temporal super-resolution. However, high-precision optical flow training datasets for medical images are challenging to produce....

Deep learning prediction of quantitative coronary angiography values using myocardial perfusion images with a CZT camera.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
PURPOSE: Evaluate the prediction of quantitative coronary angiography (QCA) values from MPI, by means of deep learning.

Deep learning-based atherosclerotic coronary plaque segmentation on coronary CT angiography.

European radiology
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...

Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
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...

Research Progress of Machine Learning and Deep Learning in Intelligent Diagnosis of the Coronary Atherosclerotic Heart Disease.

Computational and mathematical methods in medicine
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...

Automatic coronary artery segmentation and diagnosis of stenosis by deep learning based on computed tomographic coronary angiography.

European radiology
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...