Stay Informed: Transforming Radiology with Structured Reporting and Data-Driven Approaches

Dive into our activities, projects, and product updates. Catch on the latest industry news and learn who we are as a company and as a team.

Dr. Mathias Seitel

The shift towards value-based care and evidence-based medicine poses a great challenge for radiology in particular. The deliberate use of new technologies such as Artificial Intelligence is key in making this transition successful. We designed mint Lesion™ just for this purpose: a future-proof radiology workstation that combines contemporary imaging with intelligent reporting tools and thus helps radiologists assume an empowered role in the healthcare systems of tomorrow.

Related Resources

Related Resources

mint Lesion screenshot with HCC diagnosis according to APASL, AASLD, LI-RADS, KLCA-NCC, and EASL guidelines

Multicentric Study: Comparison of Diagnostic Guidelines for Hepatocellular Carcinoma

Recent advancements in MRI techniques and tumor biology have led to updated hepatocellular carcinoma (HCC) diagnostic guidelines from various liver…

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…