Bone Age Assessment of Iranian Children in an Automatic Manner
عنوان مقاله: Bone Age Assessment of Iranian Children in an Automatic Manner
شناسه ملی مقاله: JR_JMSI-11-1_003
منتشر شده در در سال 1400
شناسه ملی مقاله: JR_JMSI-11-1_003
منتشر شده در در سال 1400
مشخصات نویسندگان مقاله:
Farzaneh Dehghani - Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan
Alireza Karimian - Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan
Mehri Sirous - Department of Radiology, AL‑Zahra Hospital, Isfahan University of Medical Sciences, Isfahan
Javad Rasti - Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan
خلاصه مقاله:
Farzaneh Dehghani - Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan
Alireza Karimian - Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan
Mehri Sirous - Department of Radiology, AL‑Zahra Hospital, Isfahan University of Medical Sciences, Isfahan
Javad Rasti - Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan
Background: Bone age assessment (BAA) is a radiological process with the aim of identifying
growth disorders in children. The objective of this study is to assess the bone age of Iranian children
in an automatic manner. Methods: In this context, three computer vision techniques including
histogram of oriented gradients (HOG), local binary pattern (LBP), and scale‑invariant feature
transform (SIFT) are applied to extract appropriate features from the carpal and epiphyseal regions
of interest. Two different datasets are applied here: the University of Southern California hand atlas
for training this computer‑aided diagnosis (CAD) system and Iranian radiographs for evaluating
the performance of this system for BAA of Iranian children. In this study, the concatenation of
HOG, LBP, and dense SIFT feature vectors and background subtraction are applied to improve the
performance of this approach. Support vector machine (SVM) and K‑nearest neighbor are used here
for classification and the better results yielded by SVM. Results: The accuracy of female radiographs
is ۹۰% and of male is ۷۱.۴۲%. The mean absolute error is ۰.۱۶ and ۰.۴۲ years for female and male
test radiographs, respectively. Cohen’s kappa coefficients are ۰.۸۶ and ۰.۶, P < ۰.۰۵, for female
and male radiographs, respectively. The results indicate that this proposed approach is in substantial
agreement with the bone age reported by the experienced radiologist. Conclusion: This approach is
easy to implement and reliable, thus qualified for CAD and automatic BAA of Iranian children.
کلمات کلیدی: Bone age assessment, computer vision operators, Iranian race, K‑nearest neighbors, left‑hand radiographic images, support vector machine
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1700117/