Deep learning enables automatic adult age estimation based on CT reconstruction images of the costal cartilage.

Journal: European radiology
Published Date: May 26, 2023

Abstract

OBJECTIVE: Adult age estimation (AAE) is a challenging task. Deep learning (DL) could be a supportive tool. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method.

Authors

  • Ting Lu
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.
  • Ya-Ru Diao
    College of Computer Science, Sichuan University, Chengdu, 610064, People's Republic of China.
  • Xian-E Tang
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.
  • Fei Fan
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, China.
  • Zhao Peng
    Department of Engineering and Applied Physics, School of Physics, University of Science and Technology of China, Hefei, Anhui, China.
  • Meng-Jun Zhan
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.
  • Guang-Feng Liu
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.
  • Yu-Shan Lin
    Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States.
  • Zi-Qi Cheng
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.
  • Xu Yi
    Department of Radiology, Beidaihe Hospital, Qinhuangdao, Hebei, 066100, People's Republic of China.
  • Yu-Jun Wang
    Department of Radiology, Beidaihe Hospital, Qinhuangdao, Hebei, 066100, People's Republic of China.
  • Hu Chen
  • Zhen-Hua Deng
    West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China. dengzhenhua@scu.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals