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Background: Non-invasive imaging-based assessment of blood flow plays a critical role in evaluating heart function and structure. Computed Tomography (CT) is a widely-used imaging modality that can robustly evaluate cardiovascular anatomy…

Image and Video Processing · Electrical Eng. & Systems 2025-11-07 Jinyuxuan Guo , Gurnoor Singh Khurana , Alejandro Gonzalo Grande , Juan C. del Alamo , Francisco Contijoch

Diabetic Retinopathy (DR) refers to a barrier that takes place in diabetes mellitus damaging the blood vessel network present in the retina. This may endanger the subjects' vision if they have diabetes. It can take some time to perform a DR…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 V. Banupriya , S. Anusuya

Finite element methods (FEM) are popular approaches for simulation of soft tissues with elastic or viscoelastic behavior. However, their usage in real-time applications, such as in virtual reality surgical training, is limited by…

Machine Learning · Computer Science 2023-01-12 Mohammad Karami , Hervé Lombaert , David Rivest-Hénault

Accurate prediction of flow fields around underwater vehicles undergoing vertical-plane oblique motions is critical for hydrodynamic analysis, but it often requires computationally expensive CFD simulations. This study proposes a…

Fluid Dynamics · Physics 2026-01-07 Tianli Hu , Chengsheng Wu , Jun Ding , Xing Wang , Yu Yang , Jianchun Wang

In this study, we explore the application of an artificial recurrent neural network (RNN) called Long Short-Term Memory (LSTM) as an alternative to a turbulent Reynolds-Averaged Navier-Stokes (RANS) model. The LSTM models are utilized to…

Fluid Dynamics · Physics 2023-07-27 Hugo D. Pasinato , Nicólas F. Moguilner Reh

We introduce a novel masked pre-training technique for graph neural networks (GNNs) applied to computational fluid dynamics (CFD) problems. By randomly masking up to 40\% of input mesh nodes during pre-training, we force the model to learn…

Machine Learning · Computer Science 2025-08-27 Paul Garnier , Vincent Lannelongue , Jonathan Viquerat , Elie Hachem

Deep neural networks are being increasingly used for short-term traffic flow prediction, which can be generally categorized as convolutional (CNNs) or graph neural networks (GNNs). CNNs are preferable for region-wise traffic prediction by…

Physics and Society · Physics 2021-10-12 Wei Zeng , Chengqiao Lin , Kang Liu , Juncong Lin , Anthony K. H. Tung

Determining whether hypotensive patients in intensive care units (ICUs) should receive fluid bolus therapy (FBT) has been an extremely challenging task for intensive care physicians as the corresponding increase in blood pressure has been…

Machine Learning · Computer Science 2018-12-04 Uma M. Girkar , Ryo Uchimido , Li-wei H. Lehman , Peter Szolovits , Leo Celi , Wei-Hung Weng

This study explores the use of Federated Learning (FL) for stenosis detection in coronary angiography images (CA). Two heterogeneous datasets from two institutions were considered: Dataset 1 includes 1219 images from 200 patients, which we…

Computational fluid dynamics (CFD) is a powerful tool for modeling turbulent flow and is commonly used for urban microclimate simulations. However, traditional CFD methods are computationally intensive, requiring substantial hardware…

CFD is widely used in physical system design and optimization, where it is used to predict engineering quantities of interest, such as the lift on a plane wing or the drag on a motor vehicle. However, many systems of interest are…

Two-way coupled DNS simulation of particle-laden turbulent Couette-flow [1], in the volume fraction regime $\phi>10^{-4}$, showed a discontinuous decrease of turbulence intensity beyond a critical volume fraction…

Fluid Dynamics · Physics 2022-04-04 Swagnik Ghosh , Partha Sarathi Goswami

Coronary Artery Disease (CAD) is one of the most common forms of heart disease, which is caused by a buildup of atherosclerotic plaque (known as stenosis) in the coronary arteries, leading to insufficient supplement of blood, oxygen, and…

Computational Engineering, Finance, and Science · Computer Science 2024-09-06 Haizhou Yang , C. Alberto Figueroa , Krishna Garikipati

Accurate assessment of intraventricular blood flow is essential for evaluating hemodynamic conditions in patients supported by Left Ventricular Assist Devices (LVADs). However, clinical imaging is either incompatible with LVADs or yields…

While deep learning has shown tremendous success in a wide range of domains, it remains a grand challenge to incorporate physical principles in a systematic manner to the design, training, and inference of such models. In this paper, we aim…

Computational Physics · Physics 2020-06-16 Rui Wang , Karthik Kashinath , Mustafa Mustafa , Adrian Albert , Rose Yu

Coronary artery disease (CAD) is a leading cause of cardiovascular-related mortality, and accurate stenosis detection is crucial for effective clinical decision-making. Coronary angiography remains the gold standard for diagnosing CAD, but…

Image and Video Processing · Electrical Eng. & Systems 2025-03-25 Baixiang Huang , Yu Luo , Guangyu Wei , Songyan He , Yushuang Shao , Xueying Zeng

We perform various numerical tests to study the effect of (boundary) stenosis on blood flow stability, employing a detailed and accurate, second-order finite-volume scheme for numerically implementing a partial differential equation (PDE)…

Numerical Analysis · Mathematics 2024-08-05 Shantanu Singh , Nikolaos Bekiaris-Liberis

Intracranial arteries are critical blood vessels that supply the brain with oxygenated blood. Intracranial artery labels provide valuable guidance and navigation to numerous clinical applications and disease diagnoses. Various machine…

Image and Video Processing · Electrical Eng. & Systems 2022-11-02 Yaxin Zhu , Peisheng Qian , Ziyuan Zhao , Zeng Zeng

The acute respiratory distress syndrome (ARDS) is a severe form of hypoxemic respiratory failure with in-hospital mortality of 35-46%. High mortality is thought to be related in part to challenges in making a prompt diagnosis, which may in…

Machine Learning · Computer Science 2021-09-28 Gregory B. Rehm , Chao Wang , Irene Cortes-Puch , Chen-Nee Chuah , Jason Adams

A CFD-driven deterministic symbolic identification algorithm for learning explicit algebraic Reynolds-stress models (EARSM) from high-fidelity data is developed building on the frozen-training SpaRTA algorithm of [1]. Corrections for the…

Fluid Dynamics · Physics 2022-03-14 I. Ben Hassan SaÏdi , M. Schmelzer , P. Cinnella , F. Grasso