Smith+Nephew Case Study | Deeper Insights

Project overview

As there is a lot of complex motion and granular detail, surgery image data is very complex to analyse. Our consortium, which is comprised of Smith&Nephew Ltd, Deeper Insights and Imperial College London, won Innovate-UK funding to tackle this problem.

We developed custom Computer Vision algorithms using NN’s – Deep Learning to identify body parts in medical images. This leads to Markerless Navigation – the ability to detect where to cut bone on a knee for a knee replacement in Robotic surgery.

This results in faster than real-time image segmentation, with above 90% accuracy, of the human anatomy.