相关论文: Evaluating Uncertainties in CFD Simulations of Pat…
We propose a computational framework for vascular fluid-structure interaction (FSI), focusing on biomechanical modeling, geometric modeling, and solver technology. The biomechanical model is constructed based on the unified continuum…
Patient-specific computational modeling is a popular, non-invasive method to answer medical questions. Medical images are used to extract geometric domains necessary to create these models, providing a predictive tool for clinicians.…
In Angiographic Parametric Imaging (API), accurate estimation of parameters from Time Density Curves (TDC) is crucial. However, these estimations are often marred by errors arising from factors such as patient motion, procedural…
Interest in the application of engineering methods to problems in congenital heart disease has gained increased popularity over the past decade. The use of computational simulation to examine common clinical problems including single…
A simple but successful strategy for building a discrete diffusion operator in finite volume schemes of industrial use is to correct the standard two-point flux approximation with a term accounting for the local mesh non-orthogonality.…
This study investigates the use of High-Performance Computing (HPC) to simulate flow and transport in ultra-large micro-CT images of porous materials using Computational Fluid Dynamics (CFD). Two distinct rock samples, representative of two…
The analysis of quantitative hemodynamics and luminal pressure may add valuable information to aid treatment strategies and prognosis for aortic dissections. This work directly compared in vitro 4D-flow magnetic resonance imaging (MRI),…
The heart is the central part of the cardiovascular network. Its role is to pump blood to various body organs. Many cardiovascular diseases occur due to an abnormal functioning of the heart. A diseased heart leads to severe complications…
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…
In this work, we present a computational fluid-structure interaction (FSI) study for a healthy patient-specific pulmonary arterial tree using the unified continuum and variational multiscale (VMS) formulation we previously developed. The…
Image-based computational fluid dynamics (CFD) has emerged as a powerful tool to study cardiovascular flows while 2D echocardiography (echo) is the most widely used non-invasive imaging modality for diagnosis of heart disease. Here, echo is…
Coronary artery disease (CAD) remains the leading cause of death worldwide. Patients with suspected CAD undergo coronary CT angiography (CCTA) to evaluate the risk of cardiovascular events and determine the treatment. Clinical analysis of…
Cardiovascular diseases, particularly arrhythmias, remain a leading global cause of mortality, necessitating continuous monitoring via the Internet of Medical Things (IoMT). However, state-of-the-art deep learning approaches often impose…
This paper presents the first high-order computational fluid dynamics (CFD) simulations of static and spinning golf balls at realistic flow conditions. The present results are shown to capture the complex fluid dynamics inside the dimples…
The emergence of computational fluid dynamics (CFD) enabled the simulation of intricate transport processes, including flow in physiological structures, such as blood vessels. While these so-called hemodynamic simulations offer…
Determining brain hemodynamics plays a critical role in the diagnosis and treatment of various cerebrovascular diseases. In this work, we put forth a physics-informed deep learning framework that augments sparse clinical measurements with…
Cardiovascular disease (CVDs) is a rapidly rising global concern due to unhealthy diets, lack of physical activity, and other factors. According to the World Health Organization (WHO), primary risk factors include elevated blood pressure,…
Advancement in finite element methods have become essential in various disciplines, and in particular for Computational Fluid Dynamics (CFD), driving research efforts for improved precision and efficiency. While Convolutional Neural…
Advances in deep learning have enabled physics-informed neural networks to solve partial differential equations. Numerical differentiation using the finite-difference (FD) method is efficient in physics-constrained designs, even in…
The study is looking into the potential of using computational fluid dynamics (CFD) as a tool for predicting the outcome of surgery for alleviation of obstructive sleep apnea syndrome (OSAS). From pre- and post-operative computed tomography…