AI Backbone for Every Point Along the Radiology Workflow
With radiologists’ workload growing rapidly, a shortage of professionals in that space and increasingly demanding diagnostic requirements, radiology is one of the areas to benefit strongly from AI systems. Contextflow is developing deep learning based medical imaging tools to improve radiology workflows. The first product approved by the European regulator, contextflow SEARCH, equips radiologists with complementary information for the identification and interpretation of lung-specific image patterns in CT scans, providing a decision support system for 19 patterns as well as nodule detection. Preliminary test results show average reading time is ~30% shorter with a trend towards improved diagnostic accuracy. Contextflows’ products are seamlessly integrated into existing PACS viewer systems in hospitals and radiologists’ offices.
Contextflow was founded in 2016 by Markus Holzer, René Donner, Georg Langs and Allan Hanbury as a spin-off from Medical University Vienna (Computational Imaging Research Lab) and the Technical University of Vienna (Institute for Information Systems Engineering).
Our Investment Rationale
The company is led by a strong team of AI and medical imaging experts with longstanding experience in machine learning on medical image data and 250+ peer reviewed publications for machine learning and image processing in medical computer science. We focused our investment decision on supporting an academically strong founding team that has developed a flexible and adaptable technology suite with the potential to create a category leading company in the space of radiology.