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Physical Sciences and Mathematics Commons™
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Computer Science and Engineering Faculty Publications
Machine learning (ML), convolutional neural networks (CNN), computational fluid dynamics (CFD), optical flow method (OFM), dye perfusion, hemodynamics, least absolute shrinkage and selection operator (LASSO), angiography, cardiovascular, particle image velocimetry (PIV)
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Full-Text Articles in Physical Sciences and Mathematics
Machine Learning For Angiography-Based Blood Flow Velocity Prediction, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang
Machine Learning For Angiography-Based Blood Flow Velocity Prediction, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang
Computer Science and Engineering Faculty Publications
Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground …