top of page

About RadioEye

navigation (1).gif


About RadioEye

RadioEye was born from an expert radiologist’s desire to improve accuracy and efficiency in the interpretation of orbital radiological imaging. Finding the correct diagnosis can be a time-consuming and laborious process in daily clinical practice, especially with difficult MRI cases. Even worse, a misdiagnosis can potentially lead to costly delays in treatment, unnecessary biopsies, poor patient outcomes, and significantly higher costs to the healthcare system. Dr. Katharina Erb-Eigner, senior radiologist at Charité Hospital Berlin, RadioEye’s Founder and Chief Medical Officer, and an expert in eye and orbital MRI diagnosis, sought to increase accuracy in MRI interpretation by utilizing AI to develop a content-based image retrieval tool designed as an interactive case collection that provides curated information and a vast database of reports and radiological images of actual patient cases.


How it Works

RadioEye offers an AI-based image-search functionality to rapidly find similar cases in the extensive database based on image features alone for comparison and decision-making by the radiologist. With RadioEye, the radiologist can easily swipe through images and compare them to the case at hand. RadioEye is easily and conveniently integrated into the user’s PACS system, and accessible with only one click from the PACs screen.  



Our Alpha Trial Results¹ Show RadioEye Will Be a Game-Changer: Increasing Speed, Accuracy, and Confidence in Diagnosing MRIs

A recent retrospective study, completed in collaboration with several prestigious institutions, compared the diagnostic accuracy and time to diagnosis using RadioEye versus current standard tools. The study involved 36 independent radiologists and demonstrated that:

  • Radiologists were 2.1 times more likely to reach a correct diagnosis using RadioEye alone, and 3.7 times more likely when incorporated into the status quo.

  • Diagnostic accuracy improved by 26% with RadioEye alone and 49% when incorporated into the status quo.

  • The most significant improvement was among radiologists with no experience in reading eye and orbit MRIs, showing a 92% increase in accuracy when RadioEye is incorporated into the status quo.

  • Even experienced radiologists saw an 19% increase in accuracy when using RadioEye alone.

  • Across all experience levels and scan complexities, RadioEye users reached a correct diagnosis 73.5% of the time, compared to only 40% with STATdx.

  • Time to diagnosis was 29% faster with RadioEye alone.

  • Radiologists reported greater confidence in their diagnoses when using RadioEye.


Product Modules: Creating a “Whole-Body” Solution

RadioEye’s first product offering is an eye and orbital module, which is available now to clinical partners under a collaboration agreement, and it will be launched commercially later in 2024.  RadioEye plans to rapidly expand its software modules to cover the whole spectrum of diseases in the entire human body, with a mission to improve accuracy, confidence, and efficiency in diagnostic radiology worldwide.

RadioEye, Inc. is powered by an interdisciplinary team led by physicians, with years of experience in radiology, AI, and software development, as well as UX/UI design.

The RadioEye team is developing a whole-body, AI-powered digital application to help radiologists worldwide reach the correct diagnosis quickly and effectively. RadioEye secured initial funding from Stiftung Charité’s Investors for Health (I4H) pilot program, and the Berlin Institute of Health’s Digital Health Accelerator Program.


History of Funding

Oct. 2022 – Mar. 2024       Digital Health Accelerator Stage II, Berlin Institute of Health

Feb. 2022 - Sep.  2022     Digital Health Accelerator Stage I, Berlin Institute of Health 

Nov. 2020 - Oct. 2021        Inventors for Health (I4H) Grant, Stiftung Charité 





Let’s Work Together

Charité – Universitätsmedizin Berlin

Department of Radiology

Augustenburger Platz 1
13353  Berlin

Thanks for submitting!

bottom of page