Machine Learning System for Decision Support and Computational Automation of Early Cancer Detection and Categorisation in Colonoscopy (AIdDeCo)
The general objective of the AIdDeCo project is to develop methodologies and software tools to advance the state-of-the-art in analysis of colonoscopy data, aiding further development of efficient colonoscopy screening procedures. The project also aims to create an effective interdisciplinary research focus around endoscopic data analysis, with a network of collaborators from computing, engineering, physics and clinical disciplines, operating as a hub to co-ordinate exchange of knowledge, people and data between academic and clinical institutions.
For more information about the project and other related research please contact Professor Bogdan Matuszewski or visit the Computer Vision and Machine Learning (CVLM) webpage.
The Machine LeArnIng System for decision Support and Computational Automation of Early Cancer Detection and Categorisation in Colonoscopy (AIdDeCo) stems from the Engineering and Computational Science for Oncology Network (ECSON), originally funded by the UK Engineering and Physical Sciences Research Council (EPSRC), grant No. EP/F013698/1. ESCON has created a platform for the exchange of ideas and staff, which led to the CVML group developing interest in endoscopic data analysis resulting in successful participation in MICCAI Endoscopic Vision Grand Challenges and the recent completion of a PhD project. All these activities, and the ongoing collaborations within the ECSON, have led to the AIdDeCo project, with the funding awarded by the Science and Technology facilities Council (STFC) Cancer Diagnosis Network+ (CDN+).
Project start date: 1 November 2020
Project end date: 30 April 2022