Related papers: Attention-based Multi-fidelity Machine Learning Mo…
Early detection and diagnosis of coronary artery disease (CAD) could save lives and reduce healthcare costs. The current clinical practice is to perform CAD diagnosis through analysing medical images from computed tomography coronary…
Nowadays, with the advancement of deep neural networks (DNNs) and the availability of large-scale datasets, the face recognition (FR) model has achieved exceptional performance. However, since the parameter magnitude of the fully connected…
Aims: Coronary microvascular dysfunction (CMVD) affects approximately 40%-60% of patients with ischemia and non-obstructive coronary arteries, yet diagnosis remains challenging due to reliance on invasive functional testing or subjective…
Cardiovascular diseases (CVD) are the leading cause of death worldwide, with coronary artery disease (CAD) comprising the largest subcategory of CVDs. Recently, there has been increased focus on detecting CAD using phonocardiogram (PCG)…
Atrial Fibrillation (AF) is an abnormal heart rhythm which can trigger cardiac arrest and sudden death. Nevertheless, its interpretation is mostly done by medical experts due to high error rates of computerized interpretation. One study…
Quantification of myocardial perfusion has the potential to improve detection of regional and global flow reduction. Significant effort has been made to automate the workflow, where one essential step is the arterial input function (AIF)…
Cardiovascular diseases are among the most important causes of global mortality. Computational Fluid Dynamics (CFD) is a powerful research tool that analyzes the hemodynamics of artery and blood flow patterns. In this study, CFD simulations…
Recent development of quantitative myocardial blood flow (MBF) mapping allows direct evaluation of absolute myocardial perfusion, by computing pixel-wise flow maps. Clinical studies suggest quantitative evaluation would be more desirable…
Industrial anomaly detection (IAD) increasingly benefits from integrating 2D and 3D data, but robust cross-modal fusion remains challenging. We propose a novel unsupervised framework, Multi-Modal Attention-Driven Fusion Restoration (MAFR),…
Coronary artery stenosis is a leading cause of cardiovascular disease, diagnosed by analyzing the coronary arteries from multiple angiography views. Although numerous deep-learning models have been proposed for stenosis detection from a…
Coronary heart disease (CHD) is the leading cause of adult death in the United States and worldwide, and for which the coronary angiography procedure is the primary gateway for diagnosis and clinical management decisions. The…
This study presents a machine learning-based framework for heart disease prediction using the heart-disease dataset, comprising 303 samples with 14 features. The methodology involves data preprocessing, model training, and evaluation using…
Millions of patients suffer from rare diseases around the world. However, the samples of rare diseases are much smaller than those of common diseases. In addition, due to the sensitivity of medical data, hospitals are usually reluctant to…
Computational fluid dynamics (CFD) is a valuable tool for personalised, non-invasive evaluation of hemodynamics in arteries, but its complexity and time-consuming nature prohibit large-scale use in practice. Recently, the use of deep…
Global population aging presents increasing challenges to healthcare systems, with coronary artery disease (CAD) responsible for approximately 17.8 million deaths annually, making it a leading cause of global mortality. As CAD is largely…
Cardiovascular diseases (CVDs) are the leading causes of mortality worldwide. The contraction and relaxation of left ventricle (LV) is the main driving force of blood circulation. Altered LV hemodynamics is believed to be associated with…
During intracranial aneurysm (IA) treatment with Diverters (FDs), the device/parent artery diameters ratio may influence the ability of the device to induce aneurysm healing response. Oversized FDs are safer to deploy but may not induce…
The quantification of the coronary artery stenosis is of significant clinical importance in coronary artery disease diagnosis and intervention treatment. It aims to quantify the morphological indices of the coronary artery lesions such as…
Computational fluid dynamics (CFD) models are emerging as tools for assisting in diagnostic assessment of cardiovascular disease. Recent advances in image segmentation has made subject-specific modelling of the cardiovascular system a…
Cardiovascular Diseases (CVDs) are the leading cause of death worldwide, taking 17.9 million lives annually. Abdominal Aortic Calcification (AAC) is an established marker for CVD, which can be observed in lateral view Vertebral Fracture…