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Virginia Tech researchers using computers to detect musculoskeletal injuries

Virginia Tech University researchers are using clinical ultrasound images to train computers to detect Musculoskeletal injuries, such as small tendon tears, with the goal of facilitating more accurate medical diagnoses.
Vincent Wang, the Kevin P. Granata faculty fellow and associate professor in biomedical engineering and mechanics is conducting the research along with Carrie Cheung, a graduate student in biomedical engineering.

The research team is developing algorithms to identify ultrasound image features unique to injured tendons, according to the article. Their hope is that these algorithms can be used in clinical settings where machines can identify injuries in real-time.

These analyses may assist with clinical diagnosis and injury prevention. Musculoskeletal injuries, such as small tendon tears, can be challenging for the human eye to detect on ultrasound images, according to the article.

“Our approach resembles that used for facial recognition in commonly-used smartphone apps,” Wang said in the article.

This project is a collaboration with Bert Huang and Wu Feng in computer science at Virginia Tech for creation of algorithms and code and Albert Kozar in sports medicine at the Edward via College of Osteopathic Medicine to supply the tendon images.

Watch the video to learn more about the research.