AIMC Topic: Coronary Stenosis
Clear Filters Showing 31 to 40 of 119 articles
Non-invasive fractional flow reserve estimation using deep learning on intermediate left anterior descending coronary artery lesion angiography images.
Scientific reports
Jan 20, 2024
This study aimed to design an end-to-end deep learning model for estimating the value of fractional flow reserve (FFR) using angiography images to classify left anterior descending (LAD) branch angiography images with average stenosis between 50 and ...
A comprehensive approach to prediction of fractional flow reserve from deep-learning-augmented model.
Computers in biology and medicine
Jan 3, 2024
The underuse of invasive fractional flow reserve (FFR) in clinical practice has motivated research towards non-invasive prediction of FFR. Although the non-invasive derivation of FFR (FFR) using computational fluid dynamics (CFD) principles has becom...
CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: A clinically-inspired deep learning pipeline.
Computer methods and programs in biomedicine
Dec 21, 2023
BACKGROUND AND OBJECTIVE: The standard non-invasive imaging technique used to assess the severity and extent of Coronary Artery Disease (CAD) is Coronary Computed Tomography Angiography (CCTA). However, manual grading of each patient's CCTA according...
Deep Learning-Based Automated Labeling of Coronary Segments for Structured Reporting of Coronary Computed Tomography Angiography in Accordance With Society of Cardiovascular Computed Tomography Guidelines.
Journal of thoracic imaging
Oct 11, 2023
PURPOSE: To evaluate a novel deep learning (DL)-based automated coronary labeling approach for structured reporting of coronary artery disease according to the guidelines of the Society of Cardiovascular Computed Tomography (CT) on coronary CT angiog...
Deep learning-based coronary computed tomography analysis to predict functionally significant coronary artery stenosis.
Heart and vessels
Aug 8, 2023
Fractional flow reserve derived from coronary CT (FFR-CT) is a noninvasive physiological technique that has shown a good correlation with invasive FFR. However, the use of FFR-CT is restricted by strict application standards, and the diagnostic accur...
Stenosis Detection and Quantification of Coronary Artery Using Machine Learning and Deep Learning.
Angiology
Jul 3, 2023
The aim of this review is to introduce some applications of artificial intelligence (AI) algorithms for the detection and quantification of coronary stenosis using computed tomography angiography (CTA). The realization of automatic/semi-automatic ste...
Editorial Comment: On-Site Deep Learning-Based FFR-CT-A Novel Method to Evaluate Functionally Significant Stenosis.
AJR. American journal of roentgenology
May 3, 2023
High-Speed On-Site Deep Learning-Based FFR-CT Algorithm: Evaluation Using Invasive Angiography as the Reference Standard.
AJR. American journal of roentgenology
May 3, 2023
Estimation of fractional flow reserve from coronary CTA (FFR-CT) is an established method of assessing the hemodynamic significance of coronary lesions. However, clinical implementation has progressed slowly, partly because of off-site data transfer...
Male
Middle Aged
Deep Learning
Predictive Value of Tests
Coronary Angiography
Constriction, Pathologic
Coronary Stenosis
Female
Fractional Flow Reserve, Myocardial
Humans
Reproducibility of Results
Coronary Artery Disease
Algorithms
Aged
Reference Standards
Retrospective Studies
Computed Tomography Angiography
Coronary X-ray angiography segmentation using Artificial Intelligence: a multicentric validation study of a deep learning model.
The international journal of cardiovascular imaging
Apr 7, 2023
INTRODUCTION: We previously developed an artificial intelligence (AI) model for automatic coronary angiography (CAG) segmentation, using deep learning. To validate this approach, the model was applied to a new dataset and results are reported.
Deep Learning Model for Coronary Angiography.
Journal of cardiovascular translational research
Mar 16, 2023
The visual inspection of coronary artery stenosis is known to be significantly affected by variation, due to the presence of other tissues, camera movements, and uneven illumination. More accurate and intelligent coronary angiography diagnostic model...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823