Edward Ellis

Research Topic: Exploring novel opportunities of AI-driven methods in the management of Inflammatory Bowel Disease using intestinal ultrasound.

Supervisors: Dr Sharib Ali, Prof Andy Bulpitt, Dr Mike Byrne, Nasim Parsa.

About Edward: I graduated from the University of Sheffield with a MEng in Bioengineering. My final year project focused on using machine learning for electromyography-based gesture control of robotic devices. I then worked for 3 years as a development engineer at OxSonics Therapeutics contributing to preclinical research, regulatory document submission and First-In-Human trial. I have maintained a strong interest in AI applied to healthcare and am excited to develop my career through this CDT programme.

Project Description: Over 10 million people globally suffer from Inflammatory Bowel Disease (IBD). IBD is characterised by chronic inflammation of the gastrointestinal tract. Colonoscopy, the gold standard for diagnosing and monitoring IBD, is costly, time-consuming, invasive, and requires bowel preparation and sedation. Intestinal Ultrasound Imaging (IUS) offers a promising, affordable, non-invasive, real-time alternative. However, IUS faces challenges with limited clinical expertise globally, lack of standardised technique and high inter-operator variability. To address these challenges, this project aims to explore deep learning methods in IUS to classify IBD severity by a) automatically segmenting the bowel wall and quantifying bowel wall thickness, a key IBD indicator and b) developing a novel IUS scoring system to determine IBD severity.