Ultrasound (US) is a more cost-effective, accessible, and available imaging technique to assess anterior talofibular ligament (ATFL) injuries compared with magnetic resonance imaging (MRI). However, challenges in using this technique and increasing demand on qualified musculoskeletal (MSK) radiologists delay the diagnosis. The investigators have already developed a deep convolutional network (DCNN) model that automates detailed classification of ATFL injuries. The investigators hope to use the DCNN in real-world clinical setting to test its diagnostic accuracy.
Study Type
OBSERVATIONAL
Enrollment
400
The investigators made ultrasound examinations to the participants to test whether the model could improve their diagnostic accuracy
Peking University People's Hospital
Beijing, Beijing Municipality, China
classification of ATFL injury
ultrasound classification of ATFL injury versus surgery results
Time frame: Baseline
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