Automatic Bone Age Assessment of Adolescents Based on Weakly-Supervised Deep Convolutional Neural Networks

Automatic Bone Age Assessment of Adolescents Based on Weakly-Supervised Deep Convolutional Neural Networks

Hand bone age, as the biological age of humans, can accurately reflect the development level and maturity of individuals. Bone age assessment results of adolescents can provide a theoretical basis for their growth and development and height prediction. In this study, a deep convolutional neural netw...

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Bibliographic Details
Main Authors: Kexin Li, Jingzhe Zhang, Yunfei Sun, Xinwang Huang, Chunxue Sun, Qiancheng Xie, Shijie Cong
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Bone age assessment
deep learning
convolutional neural network
fine-grained image
Online Access:https://ieeexplore.ieee.org/document/9523857/

Internet

https://ieeexplore.ieee.org/document/9523857/

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