Automated Assessment for Bone Age of Left Wrist Joint in Uyghur Teenagers by Deep Learning
10.3969/j.issn.1004-5619.2018.01.006
- VernacularTitle:基于深度学习实现维吾尔族青少年左手腕关节骨龄自动化评估
- Author:
Ting-Hong HU
1
;
Zhong HUO
;
Tai-Ang LIU
;
Fei WANG
;
Lei WAN
;
Mao-Wen WANG
;
Teng CHEN
;
Ya-Hui WANG
Author Information
1. 司法鉴定科学研究院 上海市法医学重点实验室 上海市司法鉴定专业技术服务平台
- Keywords:
forensic anthropology;
age determination by skeleton;
carpal joints;
tomography;
X-ray;
image recognition;
deep learning;
Uyghur nationality;
adolescent
- From:
Journal of Forensic Medicine
2018;34(1):27-32
- CountryChina
- Language:Chinese
-
Abstract:
Objective To realize the automated bone age assessment by applying deep learning to digital radiography(DR)image recognition of left wrist joint in Uyghur teenagers, and explore its practical ap-plication value in forensic medicine bone age assessment. Methods The X-ray films of left wrist joint after pretreatment, which were taken from 245 male and 227 female Uyghur nationality teenagers in Uygur Autonomous Region aged from 13.0 to 19.0 years old, were chosen as subjects. And AlexNet was as a regression model of image recognition. From the total samples above, 60% of male and fe-male DR images of left wrist joint were selected as net train set, and 10% of samples were selected as validation set. As test set, the rest 30%were used to obtain the image recognition accuracy with an error range in ±1.0 and ±0.7 age respectively, compared to the real age. Results The modelling results of deep learning algorithm showed that when the error range was in ±1.0 and ±0.7 age respectively, the accuracy of the net train set was 81.4% and 75.6% in male, and 80.5% and 74.8% in female, respectively. When the error range was in ±1.0 and ±0.7 age respectively, the accuracy of the test set was 79.5% and 71.2% in male, and 79.4% and 66.2% in female, respectively. Conclusion The combination of bone age research on teenagers' left wrist joint and deep learning, which has high accuracy and good feasi-bility, can be the research basis of bone age automatic assessment system for the rest joints of body.
