17/09/2026
What if diagnosing endometriosis could take less than a second?
Researchers at Adelaide Universityโs Robinson Research Institute are helping develop a promising AI tool that could move us closer to faster, less invasive diagnosis of endometriosis.
Led by Dr Yuan Zhang, Prof Louise Hull and Associate Professor Jodie Avery, the latest research into EndoFusion explores how AI could combine information from MRI and ultrasound imaging to identify two major indicators of advanced endometriosis from a single scan.
In the latest Imagendo study, the EndoFusion method produced results in just 18 milliseconds and correctly classified cases 83% of the time, outperforming the other models evaluated in the research.
With more than 190 million women worldwide living with endometriosis, and diagnosis often taking years, developing accurate, non-invasive diagnostic methods could help shorten the pathway to answers and reduce reliance on surgery.
While the technology remains in its early stages, the findings are a promising step towards giving clinicians new tools to support faster and more accurate diagnosis.
Read more about the research and what comes next below. ๐https://adelaide.edu.au/about/news/2026/promising-ai-tool-to-speed-up-endometriosis-diagnosis/