Automatic extraction of coronary arteries using deep learning in invasive coronary angiograms [PDF]
, 2022 Accurate extraction of coronary arteries from invasive coronary angiography (ICA) is important in clinical decision-making for the diagnosis and risk stratification of coronary artery disease (CAD). In this study, we develop a method using deep learning to automatically extract the coronary artery lumen. Methods.
arxiv +1 more source
AGMN: Association Graph-based Graph Matching Network for Coronary Artery Semantic Labeling on Invasive Coronary Angiograms [PDF]
, 2023 Semantic labeling of coronary arterial segments in invasive coronary angiography (ICA) is important for automated assessment and report generation of coronary artery stenosis in the computer-aided diagnosis of coronary artery disease (CAD). Inspired by the training procedure of interventional cardiologists for interpreting the structure of coronary ...
arxiv +1 more source
Impaired coronary blood flow at higher heart rates during atrial fibrillation: investigation via multiscale modelling [PDF]
Computer Methods and Programs in Biomedicine, 175: 95-102, 2019, 2019 Background. Different mechanisms have been proposed to relate atrial fibrillation (AF) and coronary flow impairment, even in absence of relevant coronary artery disease (CAD). However, the underlying hemodynamics remains unclear. Aim of the present work is to computationally explore whether and to what extent ventricular rate during AF affects the ...
arxiv +1 more source
Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network [PDF]
arXiv, 2023 Segmentation of the coronary artery is an important task for the quantitative analysis of coronary computed tomography angiography (CCTA) images and is being stimulated by the field of deep learning. However, the complex structures with tiny and narrow branches of the coronary artery bring it a great challenge.
arxiv
Coronary Artery Semantic Labeling using Edge Attention Graph Matching Network [PDF]
, 2023 Coronary artery disease (CAD) is one of the primary causes leading deaths worldwide. The presence of atherosclerotic lesions in coronary arteries is the underlying pathophysiological basis of CAD, and accurate extraction of individual arterial branches using invasive coronary angiography (ICA) is crucial for stenosis detection and CAD diagnosis.
arxiv +1 more source
Network-Based Approach for Modeling and Analyzing Coronary Angiography [PDF]
, 2019 Significant intra-observer and inter-observer variability in the interpretation of coronary angiograms are reported. This variability is in part due to the common practices that rely on performing visual inspections by specialists (e.g., the thickness of coronaries). Quantitative Coronary Angiography (QCA) approaches are emerging to minimize observer's
arxiv +1 more source
Computed tomography coronary angiogram images, annotations and associated data of normal and diseased arteries [PDF]
arXiv, 2022 Computed Tomography Coronary Angiography (CTCA) is a non-invasive method to evaluate coronary artery anatomy and disease. CTCA is ideal for geometry reconstruction to create virtual models of coronary arteries. To our knowledge there is no public dataset that includes centrelines and segmentation of the full coronary tree.
arxiv
Hyper Association Graph Matching with Uncertainty Quantification for Coronary Artery Semantic Labeling [PDF]
arXiv, 2023 Coronary artery disease (CAD) is one of the primary causes leading to death worldwide. Accurate extraction of individual arterial branches on invasive coronary angiograms (ICA) is important for stenosis detection and CAD diagnosis. However, deep learning-based models face challenges in generating semantic segmentation for coronary arteries due to the ...
arxiv
YOLO-Angio: An Algorithm for Coronary Anatomy Segmentation [PDF]
arXiv, 2023 Coronary angiography remains the gold standard for diagnosis of coronary artery disease, the most common cause of death worldwide. While this procedure is performed more than 2 million times annually, there remain few methods for fast and accurate automated measurement of disease and localization of coronary anatomy.
arxiv
Detection and localization of Coronary Arterial Lesion with the Aid of Impedance Cardiography [PDF]
arXiv, 2020 In recent years, coronary artery disease is escalating and is likely to assume an epidemic proportion by 2030. Currently the reliable methods for detection of coronary arterial lesions are either conventional coronary angiogram (CAG) or MDCT (Multiple Detector Computed Tomography) coronary angiogram.
arxiv