Projects & Software
Current research projects
Adipose and muscular tissue segmentation
For the department of Health Evidence we are developing an application for the segmentation and quantification of adipose and muscular tissue in non-contrast abdominal CT.
Read more →AI for health
A collaboration between Radboud University and Radboudumc aimed at developing innovations based on artificial intelligence that solve clinical problems.
Read more →Brain MRI classification
In the context of the “Nationale Wetenschapsagenda” (NWA) roadmap for Value Creation through Responsible Access to and use of Big Data (VWdata) we are collecting data and setting up a challenge for the identification of healthy or abnormal MRI scans of the brain.
Read more →ICH and PHE segmentation
For the CONTRAST consortium and Dutch ICH Surgery Trial (DIST) we are developing an application for the segmentation and quantification of intracerebral hemorrhage and peri-hematomal edema in non-contrast CT.
Read more →Knee segmentation
For the Orthopedics department we are developing an application for the segmentation of the tibia, patella and fibula in non-contrast CT images of the legs.
Read more →Muscle ultrasound classification
For the Neurophysiology department we have developed an algorithm for the identification of abnormal muscle tissue in ultrasound images of the tibialis anterior.
Read more →Software
Grand-challenge.org
The home of challenges in biomedical imaging.
Ophthalmology workstation
The goal of this project is to develop a software solution that assists researchers and specialists to view and annotate retinal images.
SOL
DIAG's deep learning cluster for training and applying automated image analysis tools.