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Automatic Whole-body Bone Age Assessment Using Deep Hierarchical Features

2019-01-29
Hai-Duong Nguyen, Soo-Hyung Kim

Abstract

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

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URL

http://arxiv.org/abs/1901.10237

PDF

http://arxiv.org/pdf/1901.10237


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