ArticleScientific data2025
A dataset for quality evaluation of pelvic X-ray and diagnosis of developmental dysplasia of the hip.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Development and Application of Automated Preoperative Planning System for Developmental Dysplasia of the Hip via Keypoint Selective Integration.Journal of imaging informatics in medicine · 2026Article
- A dataset for quality evaluation of pelvic X-ray and diagnosis of developmental dysplasia of the hip.Scientific data · 2025Article
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Authors and funding
11 authors.
Funding
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Abstract
Developmental Dysplasia of the Hip (DDH) stands as one of the preeminent hip disorders prevalent in pediatric orthopedics. Automated diagnostic instruments, driven by artificial intelligence methodologies, are capable of providing substantial assistance to clinicians in the diagnosis of DDH. We have developed a dataset designated as Multitasking DDH (MTDDH), which is composed of two sub-datasets. Dataset 1 encompasses 1,250 pelvic X-ray images, with annotations demarcating four discrete regions for the evaluation of pelvic X-ray quality, in tandem with eight pivotal points serving as support for DDH diagnosis. Dataset 2 contains 906 pelvic X-ray images, and each image has been annotated with eight key points for assisting in the diagnosis of DDH. Notably, MTDDH represents the pioneering dataset engineered for the comprehensive evaluation of pelvic X-ray quality while concurrently offering the most exhaustive set of eight key points to bolster DDH diagnosis, thus fulfilling the exigency for enhanced diagnostic precision. Ultimately, we presented the elaborate process of constructing the MTDDH and furnished a concise introduction regarding its application.
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