Summary
Researchers at the Laboratory for Computational Sensing and Robotics have developed SyntheX, a system for creating realistic synthetic X-ray image data to train AI algorithms in surgical navigation techniques. The main challenge in AI-assisted surgery is acquiring highly-specific patient X-ray images and surgical tool data for training. To overcome this challenge, the researchers used domain randomization to create synthetic data with characteristics similar to real patient data. SyntheX was tested on hip x-rays and showed similar or even better performance than models trained on real patient data. SyntheX's ability to create large datasets for AI training without ethical and privacy concerns makes it a valuable tool for innovative surgical applications. The technology has potential to help surgeons plan out surgical interventions and improve patient outcomes.
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Synthetic data could be the key for AI applications in medicine (Johns Hopkins newsletter)
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