Computational modeling of cardiovascular function has become a critical part of diagnosing, treating and understanding cardiovascular disease. Most strategies involve constructing anatomically accurate computer models of cardiovascular structures, wh...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
39579454
Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatments for aortic diseases. Accurate 3D segmentation of the aorta and its branches is crucial for interventions, as inaccurate segmentation can lead to ...
OBJECTIVE: To assess the viability of using ultra-low radiation and contrast medium (CM) dosage in aortic computed tomography angiography (CTA) through the application of low tube voltage (60kVp) and a novel deep learning image reconstruction algorit...
Hemodynamic stabilization is crucial in managing acute cardiac events, where compromised blood flow can lead to severe complications and increased mortality. Conditions like decompensated heart failure (HF) and cardiogenic shock require rapid and eff...
BACKGROUND: Physics-informed neural networks (PINNs) are increasingly being used to model cardiovascular blood flow. The accuracy of PINNs is dependent on flow complexity and could deteriorate in the presence of highly-dynamical blood flow conditions...
International journal for numerical methods in biomedical engineering
39764747
The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular system diseases. But the accuracy and practicality of current estimation methods need to be improved....
BACKGROUND: The identification and measurement of aortic aneurysms is an important clinical problem. While specialized high-resolution 3D CMR sequences allow detailed aortic assessment, they are time-consuming which limits their use in screening rout...
Proceedings of the National Academy of Sciences of the United States of America
40009644
Analyzing cardiac pulse waveforms offers valuable insights into heart health and cardiovascular disease risk, although obtaining the more informative measurements from the central aorta remains challenging due to their invasive nature and limited non...
RATIONALE AND OBJECTIVES: Type 2 diabetes is a known risk factor for vascular disease with an impact on the aorta. The aim of this study was to develop a deep learning framework for quantification of aortic phenotypes from magnetic resonance imaging ...
In this work, we developed deep neural networks for the fast and comprehensive estimation of the most salient features of aortic blood flow. These features include velocity magnitude and direction, 3D pressure, and wall shear stress. Starting from 40...