Soft computing approaches for image segmentation: a survey
Image segmentation is the method of partitioning an image into a group of pixels that are
homogenous in some manner. The homogeneity dependents on some attributes like …
homogenous in some manner. The homogeneity dependents on some attributes like …
[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 …
DeepDRR–a catalyst for machine learning in fluoroscopy-guided procedures
Abstract Machine learning-based approaches outperform competing methods in most
disciplines relevant to diagnostic radiology. Interventional radiology, however, has not yet …
disciplines relevant to diagnostic radiology. Interventional radiology, however, has not yet …
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 …
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 …
A Convolutional-Transformer Model for FFR and iFR Assessment from Coronary Angiography
The quantification of stenosis severity from X-ray catheter angiography is a challenging task.
Indeed, this requires to fully understand the lesion's geometry by analyzing dynamics of the …
Indeed, this requires to fully understand the lesion's geometry by analyzing dynamics of the …
A Review of Modern Approaches for Coronary Angiography Imaging Analysis
M Popov, T Aimyshev, E Ismailov, A Bulegenov… - arXiv preprint arXiv …, 2022 - arxiv.org
Coronary Heart Disease (CHD) is a leading cause of death in the modern world. The
development of modern analytical tools for diagnostics and treatment of CHD is receiving …
development of modern analytical tools for diagnostics and treatment of CHD is receiving …
Deep learning-based end-to-end automated stenosis classification and localization on catheter coronary angiography
Background Automatic coronary angiography (CAG) assessment may help in faster
screening and diagnosis of patients. Current CNN-based vessel-segmentation suffers from …
screening and diagnosis of patients. Current CNN-based vessel-segmentation suffers from …
FeDETR: A Federated Approach for Stenosis Detection in Coronary Angiography
Assessing the severity of stenoses in coronary angiography is critical to the patient's health,
as coronary stenosis is an underlying factor in heart failure. Current practice for grading …
as coronary stenosis is an underlying factor in heart failure. Current practice for grading …
Deep learning segmentation model for automated detection of the opacity regions in the chest X-rays of the Covid-19 positive patients and the application for disease …
H Tang, N Sun, Y Li, H Xia - medRxiv, 2020 - medrxiv.org
Abstract Purpose The pandemic of Covid-19 has caused tremendous losses to lives and
economy in the entire world. The machine learning models have been applied to the …
economy in the entire world. The machine learning models have been applied to the …