Use Case

Augmedics is a medical technology company that produces the ViZOR, an augmented reality surgical visualization system that enables surgeons to view 3D images of their patients’ anatomy – giving them the equivalent of ‘X-ray vision’.

The ViZOR provides real-time tracking using infrared targets and real-time rendering on a holographic lenses to achieve a realistic and meaningful depth effect.

Before switching to Julia, tracking and rendering using OpenCV and Python required 45 milliseconds per image, resulting in 22 frames per second.

The Augmedics team wanted to increase tracking and rendering speed 3-4x to 60-90 frames per second.

So they called on Julia.

In the words of Augmedics Senior Algorithms Developer Tsur Herman,

I stumbled upon Julia and gave it a try for a few days. I fell in love with the syntax, which is in so many ways exactly how I wanted it to be. The Julia community is helpful, Juno (the interactive development environment for Julia) is super-helpful. I don’t know how one can write without it. As a result, we are achieving much more and far more efficiently using Julia.