AI-generated x-ray images fooled medical experts and improved osteoarthritis classification

Sharing medical data between laboratories and medical experts is important for medical research. However, data sharing is often sufficiently complex and sometimes even impossible due to the strict data regulatory legislation in Europe. Researchers at the University of Jyväskylä Digital Health Intelligence Laboratory addressed the problem and developed an artificial neural network that creates synthetic x-ray images that can fool even medical experts.

A group of researchers from University of Jyväskylä’s AI Hub Central Finland project developed an AI based method to create synthetic knee x-ray images to replace or complement real x-ray images in knee osteoarthritis classification.

Researchers used synthetically generated X-ray images to complement a data set of real X-ray images from the osteoarthritis study. The authenticity of the images was then assessed together with specialists from the central Finland healthcare district.

Medical experts were asked to rate osteoarthritis severity without knowing that the data set included synthetic images. In the second phase, experts tried to identify authentic and synthetic images. The results showed that on average, it was improbable even for medical experts to distinguish between real and synthetic x-ray images.

“The use of synthetic data is not subject to the same data protection regulations as real data. Using synthetic data can facilitate collaboration between, for example, research groups, companies and educational institutions,” says Sami Äyrämö, Head of Digital Health Intelligence Laboratory at the University of Jyväskylä.

According to Äyrämö, the use of synthetic data also speeds up authorisation processes and thus, among other things, testing of new ideas.

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