Bone age assessment based on deep convolution neural network incorporated with segmentation.

Journal: International journal of computer assisted radiology and surgery
Published Date:

Abstract

PURPOSE: Bone age assessment is not only an important means of assessing maturity of adolescents, but also plays an indispensable role in the fields of orthodontics, kinematics, pediatrics, forensic science, etc. Most studies, however, do not take into account the impact of background noise on the results of the assessment. In order to obtain accurate bone age, this paper presents an automatic assessment method, for bone age based on deep convolutional neural networks.

Authors

  • Yunyuan Gao
    Intelligent Control and Robotics Institute, College of Automation, Hangzhou Dianzi University, Hangzhou, China. gyy@hdu.edu.cn.
  • Tao Zhu
    Wuhan Zoncare Bio-Medical Electronics Co., Ltd, Wuhan, China.
  • Xiaohua Xu
    Kennesaw State University, Marietta, GA, 30060, USA.