Bone Age Assessment Based on Two-Stage Deep Neural Networks

Meicheng Chu · Fugen Zhou · Xiangzhi Bai · Bin Guo

17 citations0/0 files storedInternational Conference on Digital Image Computing: Techniques and Applications (DICTA)

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Forensic Anthropology and Bioarchaeology Studies Advanced Neural Network Applications Medical Imaging and Analysis

Abstract

Skeletal bone age assessment is a clinical practice to diagnose the maturity of children. To accurately assess the bone age, we proposed an automatic bone age assessment method in this paper based on deep convolution network. This method includes two stages: mask generation network and age assessment network. A U-Net convolution network with pretrained VGG16 as the encoder is used to extract the mask of bones. For the assessment module, the original images are fused together with the generated mask image to obtain segmented normalized hand bone images. We then built a multiple output convolution network for accurate age assessment. Finally, the bone age regression problem is transformed into the K-1 binary classification sub-problems. Our model was tested on RSNA2017 Pediatric Bone Age dataset. We were able to achieve the mean absolute error (MAE) of 5.98 months, which outperforms other common methods for bone age assessment. The proposed method could be used for developing fully automatic bone age assessment with better accuracy.

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1959RADIOGRAPHIC ATLAS OF SKELETAL DEVELOPMENT OF THE HAND AND WRIST 2017Fully Automated Deep Learning System for Bone Age Assessment 2009The BoneXpert Method for Automated Determination of Skeletal Maturity 2016Deep learning for automated skeletal bone age assessment in X-ray images 2007Bone age assessment of children using a digital hand atlas 2018Paediatric Bone Age Assessment Using Deep Convolutional Neural Networks 2005Hand Bone Age: A Digital Atlas of Skeletal Maturity 2017Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks

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2022Coarse-to-fine segmentation and ensemble convolutional neural networks for automated pediatric bone age assessment

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