Johannes Kast

We are committed to overcoming communication barriers within radiological departments, as well as between referring colleagues and patients, by giving everyone access to the same context.

Related Resources

Related Resources

Radiologist using for medical image analysis

Advancing Real-World Federated Learning in Radiology

Federated Learning (FL) enables collaborative model training without data centralization – a crucial aspect for radiological image analysis where…

Schematic visualization of the federated learning study and its data infrastructure

RACOON: A Guide to Bridging the Gap Between Simulated and Real-World Federated Learning Research

Deep learning (DL) has become an important part of radiological image analysis. To train these deep-learning models, access to large and diverse…

ESGAR 2024

05/28 to 05/31/2024 GOTHENBURG, SWEDEN

35th Annual Meeting and Postgraduate Course of The European Society of Gastrointestinal and Abdominal Radiology