Julia Camara Aracil, PhD
A Digitalization Approach for Wall Shear Stress Estimation
PhD Student:
Julia Cámara Aracil
PhD project title:
A Digitalization Approach for Wall Shear Stress Estimation
Supervisors:
Billy Yiu (main supervisor), Anders Bjorholm Dahl, Jorgen Arendt Jensen
Short bio:
I am a PhD student from Spain. I obtained my bachelor’s degree at the Technical University of Madrid and my master’s at DTU in biomedical engineering, where I focused on signal processing, image analysis, and the use of AI to address healthcare challenges.
Project Description:
This project aims to develop a framework for estimating wall shear stress (WSS) in the carotid artery using ultrasound, a parameter associated with plaque formation and stroke risk. Deep learning models will be used to automatically segment the vessel wall and compute blood flow velocity profiles, enabling WSS estimation.
Perspective:
In this project, we aim to demonstrate the applicability of WSS for distinguishing between healthy and diseased arteries and to bring this technology closer to potential clinical application. By enabling more reliable estimation of WSS using deep learning, this work could contribute to earlier stroke risk assessment while minimizing the manual effort required from medical professionals.