Principal Investigator: Associate Professor Esmaeil S. Nadimi
Faculty of Engineering – Maersk Mc-Kinney Moller Institute – SDU Embodied Systems for Robotics and Learning – SDU
The aim of this project is to rethink the current standard colorectal cancer (CRC) screening program and significantly improve the efficiency in terms of accuracy, acceptability, reduced complication rate and cost effectiveness.
An endoscopic camera pill produces up to 500,000 images per patient. All the recorded images are investigated manually by trained nurses which results in inefficient use of personnel. Each year, approximately 130,000 patients will go through screening. We are developing a new deep learning algorithm to fully automatise this process. ABACUS 2.0 offers the platform to handle large scale data and will be used for machine learning algorithms and big data analytics for detection of any cancer precursor, such as polyp detection, classification and characterization.