Mathematical refinements to sharpen radiation scanning systems
Australian company Southern Innovation’s patented technology was evolved from a university project designed to detect legacy landmines in war torn countries, and is now being applied in applications as diverse as cancer detection and luggage scanning.
From medical imaging to mineral processing, Australian company Southern Innovation — born from research at the University of Melbourne — is at the forefront of radiation-based scanning technologies globally.
The company’s patented technology was evolved from a university project designed to detect legacy landmines in war torn countries, and is now being applied in applications as diverse as cancer detection and luggage scanning.
Returning to the university, Southern Innovation has partnered with researchers in a new project to further refine and improve the base algorithms that underpin its scanning technology.
Professor Jonathon Manton leads the research team at the university’s Department of Electrical and Electronic Department; other team members include PhD candidate Chris McLean and mathematician Dr Michael Pauley.
Mr McLean had been chief technical officer at Southern Innovation for six years before deciding to “go back to school” for his PhD, which he says will help him to sharpen his mathematical skills, and
take the algorithms further.
The aim of the new project for Southern Innovation, which has received an Australian Research Council Linkage Grant, is to improve the speed and accuracy of signal processing from the scanning, combining the skills of both engineering and mathematics.
Signal processing theory has blossomed over more than 50 years, but there are still roadblocks in the algorithms that we need to identify and develop solutions for.
If we can get the same amount of information in less time, it obviously means we can do whatever we’re doing more quickly, for example, scanning cargo more quickly, or identifying minerals for processing.
In medicine, where speed is not necessarily the issue, the result might be to reduce the amount of radiation required for x-rays, or other imaging, he says, or to detect more minute signs of cancer even earlier in the progress of the disease.
Mr McLean says part of the challenge is to extract information from the radiation signals with algorithms that are as simple and efficient as possible. Ideally the processing software could run on something as small as a wristwatch.