The MTDDH dataset for quality evaluation of pelvic X-ray and diagnosis of developmental dysplasia of the hip

Developmental Dysplasia of the Hip (DDH) ranks among the foremost hip disorders encountered in pediatric orthopedics. Automated diagnostic tools, powered by artificial intelligence techniques, can assist clinicians in diagnosing DDH. We have constructed a dataset called MTDDH, which consists of two sub-datasets. Dataset1 consists of 1,250 pelvic X-ray images, annotated with four distinct regions for the quality evaluation of pelvic X-ray, in conjunction with eight key points for DDH diagnostic support. Dataset2 comprises 906 pelvic X-ray images, annotated exclusively with the 8 key points pertinent to DDH diagnostic assistance. MTDDH is the first dataset designed for the quality evaluation of pelvic X-rays that also provides the most extensive set of 8 key points (typically 6 key points) for aiding in DDH diagnosis, thereby meeting the need for more precise diagnostic accuracy.发育性髋关节发育不良（Developmental Dysplasia of the Hip, DDH）是小儿骨科临床中最为常见的髋关节疾病之一。基于人工智能技术的自动化诊断工具，可辅助临床医师诊断发育性髋关节发育不良。本研究构建了名为MTDDH的数据集，该数据集包含两个子数据集：子数据集1包含1250张骨盆X线片，标注了4个用于骨盆X线片质量评估的独立区域，同时同步标注了8个关键点（key points）以辅助发育性髋关节发育不良的诊断；子数据集2包含906张骨盆X线片，仅标注了用于辅助发育性髋关节发育不良诊断的8个关键点。MTDDH是首个专为骨盆X线片质量评估设计的数据集，同时提供了目前覆盖范围最广的8个关键点集（同类数据集通常仅标注6个关键点）以辅助发育性髋关节发育不良诊断，可满足更高精度的诊断准确性需求。

搜集汇总

背景与挑战

背景概述

MTDDH数据集是一个专门用于评估骨盆X光片质量和辅助诊断髋关节发育不良（DDH）的数据集，包含两个子数据集，分别标注了不同数量的关键点和区域，旨在提高诊断的精确性。