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Bone age assessment gives us evidence to analyze the children growth statusand the rejuvenation involved chronological and biological ages. All theprevious works consider left-hand X-ray image of a child in their works. Inthis paper, we carry out a study on estimating human age using whole-body boneCT images and a novel convolutional neural network. Our model with additionalconnections shows an effective way to generate a massive number of vitalfeatures while reducing overfitting influence on small training data in themedical image analysis research area. A dataset and a comparison with commondeep architectures will be provided for future research in this field.

Automatic Whole-body Bone Age Assessment Using Deep Hierarchical Features