Bone Age

Bone age assessment (BAA) determines skeletal maturity, crucial for diagnosing growth disorders and predicting adult height. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs) and vision transformers (ViTs) to analyze hand and dental radiographs, automating a previously labor-intensive process. These models aim to improve accuracy and efficiency compared to traditional atlas-based methods, with a focus on reducing computational costs and improving the robustness of predictions. Improved BAA methods offer significant benefits for pediatric care and forensic science by providing faster, more objective, and potentially more accurate age estimations.