World Class Research

 

Based on research from Prof. Alison Noble at the University of Oxford, our technology uses state-of-the-art Artificial Intelligence (AI) techniques to train our algorithms to ‘learn’ to automatically recognise anatomical features in an ultrasound image during a live scan on a patient.

 

Why AI... Why ScanNav?

 

To teach our AI algorithms, we collaborate with leading medical institutions to create large libraries of real ultrasound images that cover as wide a variety of anatomical variants as possible. This allows the AI models we create to extract salient features that allow them to distinguish normal from abnormal.

As ultrasound is an inherently noisy imaging modality, we have developed a number of image processing techniques to improve performance.

The combination of these, the size of our image libraries, and the expertise from our clinical team, puts us in a leading position to create products that support clinical decision making. These will not only reduce scanning time but also expand the use of ultrasound by giving non-specialist practitioners the support they need.

Products in the pipeline may require US FDA or other regulatory approval, as such this material should be considered informational only and does not constitute an offer to sell or infer claims or benefits.

AI solutions in development for smarter scanning
| Assist
Future product developments will include automated recognition of abnormalities in ultrasound images and the potential to enable 'at home' scanning.
AI Ultrasound Guidance and Support into the future

Protocol Based Scans

ScanNav acts as a colleague in the room by checking in real-time that images conform to protocol and that no images are missed during a scan. Our first ScanNav product focuses on obstetric scanning.

Regional Assessment Scans

ScanNav helps to make sure that pathologies are not missed during a scan with regions highlighted for further examination.