We have made several machine learning algorithms available that you can try out by uploading your own anonymised medical imaging data. Please contact us if you would like to make your own algorithm available here.

HookNet Logo

HookNet is a semantic segmentation model for histopathology whole-slide images, which combines context and details via multiple branches of encoder-decoder convolutional neural networks.


Segments pulmonary lobes and lesions and computes the CORADS and CT Severity Score from a non-contrast CT scan.

Pulmonary Lobe Segmentation Logo
Pulmonary Lobe Segmentation

Automatic segmentation of pulmonary lobes on CT scans for patients with COPD or COVID-19.

Calcium scoring Logo
Calcium scoring

Automatic detection of calcifications of the coronary arteries, the aorta and the aortic and mitral valves in CT scans.

Gleason Grading of Prostate Biopsies Logo
Gleason Grading of Prostate Biopsies

Automated Gleason grading of prostate biopsies following the Gleason Grade Group system.

CXR Cardiomegaly Detection Logo
CXR Cardiomegaly Detection

Detect cardiomegaly on chest radiographs through the segmentation of the heart and lungs .

Tissue-Background Segmentation Logo
Tissue-Background Segmentation

Tumor Detection in Lymph Nodes Logo
Tumor Detection in Lymph Nodes

Vertebra segmentation and labeling Logo
Vertebra segmentation and labeling

Spleen Segmentation Logo
Spleen Segmentation

Automatic spleen segmentation on thorax-abdomen CT scans.