Research Progress of Age Estimation in the Living by Knee Joint MRI.
10.12116/j.issn.1004-5619.2022.220503
- Author:
Hong-Xia HAO
1
;
Ya-Hui WANG
2
;
Zhi-Lu ZHOU
3
;
Tai-Ang LIU
4
;
Jin CHEN
4
;
Yu-Heng HE
4
;
Lei WAN
2
;
Wen-Tao XIA
2
Author Information
1. Key laboratory of Microecology-Immune Regulatory Network and Related Diseases, School of Basic Medicine, Jiamusi University, Jiamusi 154007, Heilongjiang Province, China.
2. Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China.
3. Department of Forensic Medicine, Guizhou Medical University, Guiyang 550009, China.
4. Shanghai Fanyang Information Technology Co., Ltd, Shanghai 200444.
- Publication Type:Journal Article
- Keywords:
age estimation;
deep learning;
forensic anthropolgy;
knee joint;
magnetic resonance imaging;
review
- MeSH:
Epiphyses/diagnostic imaging*;
Age Determination by Skeleton/methods*;
Reproducibility of Results;
Magnetic Resonance Imaging/methods*;
Knee Joint/diagnostic imaging*
- From:
Journal of Forensic Medicine
2023;39(1):66-71
- CountryChina
- Language:English
-
Abstract:
Bone development shows certain regularity with age. The regularity can be used to infer age and serve many fields such as justice, medicine, archaeology, etc. As a non-invasive evaluation method of the epiphyseal development stage, MRI is widely used in living age estimation. In recent years, the rapid development of machine learning has significantly improved the effectiveness and reliability of living age estimation, which is one of the main development directions of current research. This paper summarizes the analysis methods of age estimation by knee joint MRI, introduces the current research trends, and future application trend.
