Blood vessel segmentation algorithms—review of methods, datasets and evaluation metrics
Background Blood vessel segmentation is a topic of high interest in medical image analysis
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
A recurrent CNN for automatic detection and classification of coronary artery plaque and stenosis in coronary CT angiography
Various types of atherosclerotic plaque and varying grades of stenosis could lead to different
management of patients with a coronary artery disease. Therefore, it is crucial to detect and …
management of patients with a coronary artery disease. Therefore, it is crucial to detect and …
Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed …
Though conventional coronary angiography (CCA) has been the standard of reference for
diagnosing coronary artery disease in the past decades, computed tomography …
diagnosing coronary artery disease in the past decades, computed tomography …
Imagecas: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images
Cardiovascular disease (CVD) accounts for about half of non-communicable diseases.
Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed …
Vessel stenosis in the coronary artery is considered to be the major risk of CVD. Computed …
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 …
Fusing 2D and 3D convolutional neural networks for the segmentation of aorta and coronary arteries from CT images
L Gu, XC Cai - Artificial Intelligence in Medicine, 2021 - Elsevier
Automated segmentation of three-dimensional medical images is of great importance for the
detection and quantification of certain diseases such as stenosis in the coronary arteries …
detection and quantification of certain diseases such as stenosis in the coronary arteries …
Automatic segmentation, detection and quantification of coronary artery stenoses on CTA
Accurate detection and quantification of coronary artery stenoses is an essential
requirement for treatment planning of patients with suspected coronary artery disease. We …
requirement for treatment planning of patients with suspected coronary artery disease. We …
Automatic coronary wall and atherosclerotic plaque segmentation from 3D coronary CT angiography
AM Ghanem, AH Hamimi, JR Matta, A Carass… - Scientific reports, 2019 - nature.com
Coronary plaque burden measured by coronary computerized tomography angiography
(CCTA), independent of stenosis, is a significant independent predictor of coronary heart …
(CCTA), independent of stenosis, is a significant independent predictor of coronary heart …
Coronary artery segmentation in cardiac CT angiography using 3D multi-channel U-net
YC Chen, YC Lin, CP Wang, CY Lee, WJ Lee… - arxiv preprint arxiv …, 2019 - arxiv.org
Vessel stenosis is a major risk factor in cardiovascular diseases (CVD). To analyze the
degree of vessel stenosis for supporting the treatment management, extraction of coronary …
degree of vessel stenosis for supporting the treatment management, extraction of coronary …
Fast level‐set based image segmentation using coherent propagation
Purpose: The level‐set method is known to require long computation time for 3D image
segmentation, which limits its usage in clinical workflow. The goal of this study was to …
segmentation, which limits its usage in clinical workflow. The goal of this study was to …