Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip

Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip

Abstract Objectives Anteroposterior pelvic radiographs remains the most widely employed method for diagnosing developmental dysplasia of the hip. This study aims to evaluate the accuracy of an artificial intelligence model in measuring angles in pelvic radiographs of the hip. The assessment seeks to...

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Bibliographic Details
Main Authors: Ruixin Li, Xiao Wang, Tianran Li, Beibei Zhang, Xiaoming Liu, Wenhua Li, Qirui Sui
Format: Article
Language:English
Published: BMC 2024-11-01
Series:BMC Musculoskeletal Disorders
Subjects:
Developmental dysplasia of the hip
Artificial intelligence
Deep learning
Pelvic radiograph
Online Access:https://doi.org/10.1186/s12891-024-08035-3
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