Towards more accurate diagnostics in healthcare: AI applied to super-resolution ultrasound imaging

Ultrasound imaging is widely used in clinical settings as it is inexpensive, portable, real-time, and does not involve ionizing radiation. However, the quality of ultrasound images is often poor, leading to low diagnosis capabilities. The aim of this project is to leverage the potential of artificial intelligence, specifically of deep learning, to improve the quality of ultrasound images, in particular through the use of super-resolution ultrasound imaging. This will enable clinicians to identify pathologies and potentially start treatment at an earlier stage. A second step of the project is to use deep learning to diagnose diseases automatically using super-resolved ultrasound scans. The project will set up a long-term collaboration between experts from three Una Europa Universities: KU Leuven, the University of Edinburgh, and the Universidad Complutense de Madrid.