Generating wall shear stress for coronary artery in real-time using neural networks: Feasibility and initial results based on idealized models
Authors:
- 1 November 2020
- journal article
- research article
- Published by Elsevier in Computers in Biology and Medicine
- Vol. 126, 104038
Abstract
No abstract availableKeywords
This publication has 26 references indexed in Scilit:
- Computational Fluid Dynamics Applied to Cardiac Computed Tomography for Noninvasive Quantification of Fractional Flow ReserveJACC, 2013
- Association of Coronary Wall Shear Stress With Atherosclerotic Plaque Burden, Composition, and Distribution in Patients With Coronary Artery DiseaseJournal of the American Heart Association, 2012
- Automated macular pathology diagnosis in retinal OCT images using multi-scale spatial pyramid and local binary patterns in texture and shape encodingMedical Image Analysis, 2011
- Patient-Specific Modeling of Blood Flow and Pressure in Human Coronary ArteriesAnnals of Biomedical Engineering, 2010
- Vortex formation and recirculation zones in left anterior descending artery stenoses: computational fluid dynamics analysisPhysics in Medicine & Biology, 2010
- Simulation of cardiac motion on non-Newtonian, pulsating flow development in the human left anterior descending coronary arteryPhysics in Medicine & Biology, 2008
- Reducing the Dimensionality of Data with Neural NetworksScience, 2006
- The Curse of Dimensionality in Data Mining and Time Series Prediction2005
- Learning representations by back-propagating errorsNature, 1986
- Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in positionBiological Cybernetics, 1980