Endoscopy is used to diagnose and monitor disease progression in hollow organs (oesophagus, stomach, colorectal, bladder and ureter, uterus, and peritoneum). Endoscopy remains highly operator dependent with concerns on quality of surveillance and variability in patient outcomes. Both effective patient treatment and minimising associated economic burden is of high importance. Diseases such as Inflammatory Bowel Disease (IBD) require patient monitoring over time and have a higher risk of developing colorectal cancer. IBD is characterised by symptomatic relapse and remission, requiring frequent endoscopic surveillance and risk monitoring through lesion and dysplasia identification. Monitoring and assessing disease progression and measuring response to drug therapy is critical in effective management of IBD. The project will aim at developing deep learning methods for - a) quantifying severity of IBD based on clinically established scoring systems and b) longitudinal comparison using localised 3D maps.