Cameras are everywhere these days: capturing everyday moments, recording exceptional events and objects, and helping doctors take a closer look at our bodies when we’re sick. But while we’re very good at collecting this information, it can be hard find a particular file later or to spot an abnormality in a medical scan.
Matthew Kyan, professor of electrical engineering and computer science at York University’s Vision: Science to Applications (VISTA) program, uses machine learning and pattern recognition to make photos and videos easier to retrieve when we need them.
Beyond home videos and selfies, Kyan’s interdisciplinary collaborations are making big contributions from historical archives and archeology to health and medicine.
“We work with filmmakers, working on cultural heritage types of projects,” says Kyan. “We’re looking through large archives of historical data. We also work with archeologists, digitizing and storing large collections of artifacts to build tools that can more effectively allow them to query these large databases.”
Digitizing a searchable database of important historical and archeological objects makes it possible for people all over the world to study them. 3D models even make it possible to interact with objects on a screen or using VR.
Kyan’s tools can also be used to analyze medical images for abnormalities, even when a medical professional isn’t sure what to look for.
“We work with doctors, looking for a tumour within a CT scan or being able to identify a valve within the heart that has been malformed,” explains Kyan. “Or, if it’s an MRI scan, to search for something within the brain that is pathological; it’s not something that would commonly be found, there’s not a model for how to find it.”
What’s exciting is that while the tools can assist a healthcare team in identifying potential problems, the process is still driven by a human user, and that makes the process adaptable. And finding a problem feeds back into the process for future patients, as doctors learn more about a pathology that was previously unknown.
Looking more deeply into the volumes of information we collect ultimately helps us shape our understanding of everything from human and natural history to the future of healthcare.