MedTech company Odin Vision has announced it will scale up its cancer detection technology.
The firm recently received investment from a round led by the UCL Technology Fund alongside London Co-Investment Fund (LCIF) and AI seed and grant funding from InnovateUK, the NHS and the UK Space Agency and European Space Agency.
Led by Peter Mountney and Danail Stoyanov (UCL Computer Science), the company is developing an artificial intelligence (AI) system to improve early detection and diagnosis of bowel cancer.
The new software tool identifies and characterises polyps by analysing live colonoscopy video, leading to early treatment.
The technology uses advanced machine learning algorithms specifically designed for medical data. The company is also focused on developing a scalable real time healthcare system that uses cloud computing and satellite communications to support doctors in their decision making.
Odin Vision aims to use the investment to improve the accuracy and usability of its software through a proof of concept phase.
“Odin Vision presents an exciting opportunity in a fast-paced area of the medtech landscape,” said David Grimm, investment director at UCL Technology Fund.
“Its innovative software has the potential to save millions of pounds for the NHS, as well as offering medical treatment that clinicians can have greater conviction in.
“I look forward to working with Peter, Danail and the Odin Vision team as their technology is taken through the next phase of development. This is our first investment into a company created through UCLB’s innovative Portico Venture Programme and we look forward to supporting many more.”
Pete Mountney, CEO of Odin Vision, added: “The UCL team of computer scientists, engineers and clinicians have developed and refined this amazing technology over a number of year and this investment comes at a crucial time for the company as we prepare to bring this technology into the hospital.
“It is a very exciting time in healthcare where there are significant opportunities to develop technology that can lead to better patient outcomes and save healthcare payers money.”