Analysis of breast and prostate cancer with artificial intelligence for improved care

The cancer grade, provided by pathologists, is the most important predictor of patient outcome, but suffers from inter- and intra-pathologist variability, reducing its usefulness for individual patients. An expert-level AI system will be provided to support pathologist and help reduce this variability and make their diagnostic practice more accurate and efficient.

Digital Eye Health; towards remote monitoring in eyecare

A successful societal uptake of digital eye health requires a robust and safe telemonitoring platform that addresses the needs of its users. Patients request a simple tool that works intuitively with little external instructions. Doctors need a dataflow fully integrated in the electronic health record, and both need to develop trust in the validity and safety of remote monitoring. These requirements are addressed in this project.

Transmission scanning for accurate magnetic resonance positron emission tomography

Photon attenuation correction methods for PET-MRI are currently developed using CT transmission images obtained prior to the PET-MRI scan. Their accuracy is limited by differences due to patient movement. A transmission scan mechanism will be integrated into the PET-MRI system, capable of acquiring transmission images simultaneously during the PET-MRI scan.

Automatic recognition of anatomical structures to reduce animal experiments

Artificial intelligence is currently revolutionising many fields of research, and it is proposed to use it to drastically reduce the number of animals used for medical experimentation. This will be done by developing artificial intelligence methods to recognise automatically anatomical structures in animals, which is important in many disease models.