Diagnostic Image Analysis Group

The Diagnostic Image Analysis Group is part of the Departments of Radiology and Nuclear Medicine, Pathology, and Ophthalmology of Radboud University Medical Center. We develop computer algorithms to aid clinicians in the interpretation of medical images and thereby improve the diagnostic process.

The group has its roots in computer-aided detection of breast cancer in mammograms, and we have expanded to automated detection and diagnosis in breast MRI, ultrasound and tomosynthesis, chest radiographs and chest CT, prostate MRI, neuro-imaging and the analysis of retinal and digital pathology images. The technology we primarily use is deep learning.

It is our goal to have a significant impact on healthcare by bringing our technology to the clinic. We are therefore fully certified to develop, maintain, and distribute software for analysis of medical images in a quality controlled environment (MDD Annex II and ISO 13485).

On this site you find information about the history of the group and our collaborations, an overview of people in DIAG, current projects, publications and theses, contact information, and info for those interested to join our team.


September, 2019

Opening ICAI.jpg

On the 16th of September the official opening event of the Thira Lab and Radboud AI for Health Lab look place in the Tuinzaal of Radboudumc. Witnessed by many interested attendees, Radboudumc’s Chair of the Executive Board prof. Paul Smits opened the first two Nijmegen-based labs within the nationwide Innovation Center of Artificial Intelligence (ICAI).

Thira Lab

Thira Lab is a collaboration between Radboudumc and Thirona, a spin-out company from Radboudumc, and Delft Imaging Systems, a company developing healthcare solutions for the specific needs of vulnerable communities around the world. In Thira Lab, nine Ph.D. candidates and post-docs from Radboudumc work on deep learning image analysis of CT scans, radiographs and retinal images.

Radboud AI for Health

Radboud AI for Health Lab is a new collaboration between Radboud University and Radboudumc, and is part of Radboud AI, a campus-wide initiative to improve collaboration and start new projects with AI researchers in Nijmegen. Radboud AI for Health has awarded 6 Ph.D. positions, aimed to bring a variety of AI solutions to the clinic. Radboud AI for Health, located in the Radboudumc Innovation Space, will also house BSc and MSc students who perform AI research projects in collaboration with Radboudumc clinicians. Finally, the Lab offers courses to Radboudumc employees who would like to learn more about the application of AI in healthcare.

More Research Highlights.


  • June 12, 2020 - June 12, During the Euroson 2020 webinar, Thomas van den Heuvel won the Young Investigator Award from the European Federation of Societies for Ultrasound in Medicine and Biology with his abstract entitled: “Introducing prenatal ultrasound screening in research-limited settings using artificial intelligence”.
  • March 18, 2020 - The defense of Midas Meijs' PhD thesis titled 'Automated Image Analysis and Machine Learning to Detect Cerebral Vascular Pathology in 4D-CTA' has been postponed because of COVID19. A new date will follow.

More News.