Current state and future perspectives of artificial intelligence for automated coronary angiography imaging analysis in patients with ischemic heart disease
MA Molenaar, JL Selder, J Nicolas, BE Claessen… - Current cardiology …, 2022 - Springer
Abstract Purpose of Review Artificial intelligence (AI) applications in (interventional)
cardiology continue to emerge. This review summarizes the current state and future …
cardiology continue to emerge. This review summarizes the current state and future …
[HTML][HTML] Automatic stenosis recognition from coronary angiography using convolutional neural networks
Background and objective: Coronary artery disease, which is mostly caused by
atherosclerotic narrowing of the coronary artery lumen, is a leading cause of death …
atherosclerotic narrowing of the coronary artery lumen, is a leading cause of death …
Automatic detection of coronary artery stenosis by convolutional neural network with temporal constraint
Coronary artery disease (CAD) is a major threat to human health. In clinical practice, X-ray
coronary angiography remains the gold standard for CAD diagnosis, where the detection of …
coronary angiography remains the gold standard for CAD diagnosis, where the detection of …
Stenosis-DetNet: Sequence consistency-based stenosis detection for X-ray coronary angiography
Background The automatic detection of coronary artery stenosis on X-ray images is
important in coronary heart disease diagnosis. Conventional methods cannot accurately …
important in coronary heart disease diagnosis. Conventional methods cannot accurately …
Automated identification and grading of coronary artery stenoses with X-ray angiography
Background and Objective X-ray coronary angiography (XCA) remains the gold standard
imaging technique for the diagnosis and treatment of cardiovascular disease. Automatic …
imaging technique for the diagnosis and treatment of cardiovascular disease. Automatic …
Automated stenosis detection and classification in x-ray angiography using deep neural network
C Cong, Y Kato, HD Vasconcellos… - 2019 IEEE …, 2019 - ieeexplore.ieee.org
This paper proposes a deep-learning based workflow for stenosis classification and
localization on coronary angiography images of 194 patients from a multi-center study …
localization on coronary angiography images of 194 patients from a multi-center study …
Automated characterization of stenosis in invasive coronary angiography images with convolutional neural networks
B Au, U Shaham, S Dhruva, G Bouras, E Cristea… - arXiv preprint arXiv …, 2018 - arxiv.org
The determination of a coronary stenosis and its severity in current clinical workflow is
typically accomplished manually via physician visual assessment (PVA) during invasive …
typically accomplished manually via physician visual assessment (PVA) during invasive …
Fast retinal vessel tree extraction: A pixel parallel approach
Early ocular disease diagnosis is an important field in medical research. From the image
processing point of view, many strategies and algorithms have been developed to deal with …
processing point of view, many strategies and algorithms have been developed to deal with …
Automatic detection of coronary stenosis in X-ray angiography through spatio-temporal tracking
CB Compas, T Syeda-Mahmood… - 2014 IEEE 11th …, 2014 - ieeexplore.ieee.org
Automatic detection of coronary stenosis in X-ray angiography data is a challenging
problem. The low contrast between vessels and surrounding tissue, as well as large …
problem. The low contrast between vessels and surrounding tissue, as well as large …
A level set method for vessel segmentation in coronary angiography
This paper presents a level set technique to extract the vascular structures in coronary
angiography. It makes use of the Mumford-Shah functional to extract contours that are not …
angiography. It makes use of the Mumford-Shah functional to extract contours that are not …