About us

Research-driven AI for radiology

jung radiology is a spin-off of jung diagnostics GmbH, combining years of experience in neuroradiological image analysis with the goal of bringing AI into clinical practice in a genuinely usable way.

Our origin

From diagnostics to a marketplace

For years, jung diagnostics has supported patient care through computer-assisted analysis of neuroradiological data — in collaboration with radiological reference centers and university hospitals.

jung radiology takes this further: we bundle vetted AI modules from different vendors into a vendor-neutral marketplace and integrate them into PACS and RIS through standardized interfaces. Many individual applications become one continuous, traceable reporting environment.

2009
jung diagnostics
founded
4
Modalities
covered today
DICOM
+ HL7
standard interfaces
HH
Hamburg
location
What we stand for

Our principles

Clinical evidence

Our methods emerge from research with university hospitals and are approved as medical devices.

Vendor neutrality

We curate in-house and external modules to our customers' requirements — without lock-in.

Traceability

AI results must remain reviewable. Transparency and control are central to us.

30
MINUTES PER SESSION

Focused sessions to discuss individual cases — easy to fit into the clinical day without much effort.

Support

Training builds trust in the AI results

Transparency comes not from good algorithms alone, but from understanding. Our training sessions make the AI results traceable — compact and tailored to your needs.

  • Improve traceability of AI results — create transparency
  • Discussion of individual cases from your practice
  • Arranged at short notice and as needed
Request training
Part of the jung family

A spin-off of jung diagnostics GmbH

Since 2009, jung diagnostics has supported patient care through computer-assisted analysis of neuroradiological data — for example, in the early detection of Alzheimer's and other forms of dementia, and in treatment guidance for multiple sclerosis.

Together with university hospitals, new methods are continuously researched and — once successfully validated — translated into medical devices for patient care.

Get to know us

Talk to us about your radiology environment and the right AI modules.

Get in touch