AE-BoNet: A Deep Learning Method for Pediatric Bone Age Estimation using an Unsupervised Pre-Trained Model.

Journal: Journal of biomedical physics & engineering
Published Date: Jun 1, 2025

Abstract

BACKGROUND: Accurate bone age assessment is essential for determining the actual degree of development and indicating a disorder in growth. While clinical bone age assessment techniques are time-consuming and prone to inter/intra-observer variability, deep learning-based methods are used for automated bone age estimation.

Authors

  • Mojtaba Sirati-Amsheh
    Department of Medical Physics, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Elham Shabaninia
    Department of Applied Mathematics, Faculty of Sciences and Modern Technologies, Graduate University of Advanced Technology, Kerman, Iran.
  • Ali Chaparian
    Department of Medical Physics, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

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