Skip to content

Industrial Doctoral Thesis: Applications of deep learning techniques in Magnetic Resonance Imaging for Multiple Sclerosis: from research innovations to clinical implementation

March 6, 2025

By: Liliana Valencia Rodríguez
Supervised by:  Dr. Xavier Lladó, Universitat de Girona / Dr. Sergi Valverde, Tensormedical / Dr. Arnau Oliver, Universitat de Girona

 

Abstract:

This thesis explores how advanced artificial intelligence techniques, specifically deep learning, can improve the analysis of brain scans (MRI) for people with multiple sclerosis (MS) in the clinical practice.

The study focuses on three key areas. First, it introduces a new AI tool designed to accurately and consistently isolate the brain from the surrounding tissues in MRI scans. This is crucial for many analyses and can improve the accuracy of brain volume measurements, which are important for tracking disease progression. Secondly, the research develops a method to generate synthetic brain scans from existing ones. This can help improve the detection of MS lesions (areas of brain damage) while potentially reducing the need for expensive and time-consuming MRI scans.

Finally, the study investigates the practical challenges of bringing these AI tools into real-world clinical use. This includes navigating regulations and ensuring the safety and effectiveness of these technologies for patients.

In summary, this research aims to improve the diagnosis and management of MS by developing and implementing innovative AI solutions for analyzing brain MRI scans.

 

 

 

Share it!

More News

VIBOT
June 6, 2014

VIBOT Erasmus Mundus Master gets “International Master Distinction” from the Catalan Government

News

EURM_KOM
March 6, 2018

EU Marine Robots Kick Off meeting takes place in Porto

Projects, Underwater Robotics

Forum Industrial
April 20, 2023

Vicorob coordinates Two Erasmus Mundus Masters Programs in Robotics and Underwater Technologies

News

thesis-filip
October 7, 2016

Clinical decision support for screening, diagnosis and assessment of respiratory diseases: Chronic obstructive pulmonary disease as a use case.

Medical Imaging Lab, News, Scientific Results