PediURF, A Comprehensive X-ray Dataset for The Pediatric Ulna and Radius Fractures Analysis

Pediatric foream fractures, particularly involving the ulna and radius, are among the most common childhood injuries. However, the lack of standardized and openly available datasets has limited progress in artificial intelligence research and constrained clinical validation. To address this issue, we present the Pediatric Ulna and Radius Fractures (PediURF) dataset, which was collected with detailed annotations by expert radiologists across proximal, midshaft, and distal fracture types. By releasing PediURF, we aim to provide an accessible resource for algorithm development, benchmarking, and clinical training. To validate its utility, we developed URFNet, a dual-view classification model designed to integrate anteroposterior and lateral perspectives. Compared with other baseline models, the proposed model achieved the best performance. Therefore, this work provides a valuable foundation for future deep learning-based studies in pediatric fracture classification.