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.
Last week, the final meeting of the AMI-project took place at the Radiology and Pathology department of Radboud University Medical Center. The AMI-project was a close collaborative project between the Diagnostic Image Analysis Group and the Fraunhofer Institute for Digital Medicine MEVIS. The aim of AMI was to develop a generic platform for automatic medical image analysis. Deep learning-based algorithms have successfully been developed for the automated analysis and registration of chest CTs, ophthalmology images and histological whole slide images. The web-based viewing system, specifically developed for, but not restricted to this project, offers support for multiple radiology, ophthalmology and pathology image formats. The AMI-project was funded by the Radboud University, Radboud University Medical Center and the Fraunhofer Gesellschaft as an ICON-project, focusing on collaborative, interdisciplinary and international research.
More Research Highlights.