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Deep-learning Enabled Ultrasound Diagnosis of Anterior Talofibular Ligament Injury

Ultrasound Clinical Trial

Official title:
Deep Learning-enabled Ultrasound Classification of Anterior Talofibular Ligament Injury in China: A Prospective, Multicentre, Diagnostic Study

Clinical Trial Summary

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.

Clinical Trial Description

n/a

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT06373029
Study type Observational
Source Peking University People's Hospital
Contact Jiaan Zhu, Dr
Phone +8613581902236
Email canzhujia@126.com
Status Not yet recruiting
Phase
Start date April 20, 2024
Completion date December 30, 2025
View Details
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