Automated assessment of developmental levels of epiphysis by support vector machine.
- Author:
Ya-hui WANG
;
Zi-shen WANG
;
Hua WEI
;
Lei WAN
;
Chong-liang YING
;
Guang-you ZHU
- Publication Type:Journal Article
- MeSH:
Adolescent;
Bone Development/physiology*;
Child;
Epiphyses/growth & development*;
Female;
Humans;
Image Processing, Computer-Assisted/methods*;
Male;
Radius/growth & development*;
Support Vector Machine;
Ulna/growth & development*;
Wrist/growth & development*;
Wrist Joint/growth & development*;
Young Adult
- From:
Journal of Forensic Medicine
2014;30(6):422-426
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To realize the automated assessment of the levels of epiphysis of distal radius and ulna by support vector machine (SVM).
METHODS:The X-ray films of the left wrist joints were taken from 140 teenagers aged from 11 to 19 years old as training samples. The levels of epiphysis of distal radius and ulna were divided into five developmental levels. Each level contained 28 samples. Another 35 cases were selected as independent verifying samples. SVM classification models of the five developmental levels of epiphysis of distal radius and ulna were established. The internal cross validation was made by leave one out cross validation (LOOCV), while the external validation was made by histogram of oriented gradient (HOG), and then the accuracy (PA) of testing results was calculated, respectively.
RESULTS:The PA of SVM, LOOCV and HOG of distal radius epiphyseal level were 100%, 78.6%, and 82.8%, respectively; whereas the PA of SVM, LOOCV and HOG of distal ulna epiphyseal level were 100.0%, 80.0% and 88.6%, respectively.
CONCLUSION:The SVM-based automatic models of the growth stage of distal ra- dius and ulna appear to have certain feasibility, and may provide a foundation for software development of bone age assessment by forensic medicine.
