The present work is about the application of wall shear stress descriptors–time averaged
wall shear stress (TAWSS), oscillating shear index (OSI) and relative residence time (RRT) …

Background The objectives of this study were to develop a 3D convolutional deep learning
framework (CarotidNet) for fully automatic segmentation of carotid bifurcations in computed …

Segmentation of brain aneurysm is of paramount importance in aneurysm treatment
planning. However, the segmentation of intensity varying and low-contrast cerebral blood …

Clinical evidence has shown that hemodynamics plays an important role in vascular
diseases that hemodynamic parameters are highly dependent on the elasticity of the artery …

Purpose This study aimed to propose a method to semi-automatically segment lumen of
carotid artery on TOF-MRA images with well performance on images with weak boundary …

Background Patient-specific modelling in clinical studies requires a realistic simulation to be
performed within a reasonable computational time. The aim of this study was to develop …

Background and objective Due to the relatively low fluid velocities in major arteries and
veins, blood flow is by default laminar, however, turbulence can occur as a result of stenosis …

Local post-stenotic hemodynamics has critical influence in the atherosclerotic plaque
progression occurring in susceptible arterial sites, in particular the left main coronary artery …

Automatic segmentation of the arterial lumen from ultrasound images is an important task in
clinical diagnosis. Carotid artery recognition, the first task in lumen segmentation, should be …

Investigation of the carotid artery plays an important role in the diagnosis of cerebrovascular
events. Segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images is …