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.

AI for health

A collaboration between Radboud University and Radboudumc aimed at developing innovations based on artificial intelligence that solve clinical problems.

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.

Coronary artery segmentation

For the department of Cardiology we are developing an application for the segmentation of coronary arteries in cardiac OCT recordings.

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.

Quantifying IHC pathology stains

For the Pathology department we are developing an application that can unmix different IHC stains to aid analysist in quantifying pathology scans.

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.

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.