Bone age determination in young children (newborn to 6 years old) using support vector machines

Basit Öğe Kaydı
dc.contributor.authorGuraksin, Gur Emre
dc.contributor.authorUguz, Harun
dc.contributor.authorBaykan, Omer Kaan
dc.date.accessioned2020-03-26T19:23:13Z
dc.date.available2020-03-26T19:23:13Z
dc.date.issued2016
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractBone age is assessed through a radiological analysis of the left-hand wrist and is then compared to chronological age. A conflict between these two values indicates an abnormality in the development process of the skeleton. This study, conducted on children aged between 0 and 6 years, proposes a computer-based diagnostic system to eliminate the disadvantages of the methods used in bone age determination. For this purpose, primarily an image processing procedure was applied to the X-ray images of the left-hand wrist of children from different ethnic groups aged between 0 and 6 years. A total of 9 features, corresponding to the carpal bones and distal epiphysis of the radius bone with some physiological attributes of the children, were obtained. Then, by using gain ratio, the best 6 features were used for the classification process. Next, the bone age determination process was performed with the obtained features with the help of the support vector machine (SVM), naive Bayes, k-nearest neighborhood, and C4.5 algorithms. Finally, the features used in the determination process and their effects on the accuracies were examined. The results of the designed system showed that SVM method has a better achievement rate than the other methods at a rate of 72.82%. Additionally, in this study, a new feature corresponding to the distance between the centers of gravity of the carpal bones was used for the classification process, and the analysis of the related feature showed that there was a statistically significant difference at P < 0.05 between this feature and bones in children aged between 0 and 6 years.en_US
dc.identifier.doi10.3906/elk-1305-271en_US
dc.identifier.endpage1708en_US
dc.identifier.issn1300-0632en_US
dc.identifier.issn1303-6203en_US
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1693en_US
dc.identifier.urihttps://dx.doi.org/10.3906/elk-1305-271
dc.identifier.urihttps://hdl.handle.net/20.500.12395/33317
dc.identifier.volume24en_US
dc.identifier.wosWOS:000374121500071en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEYen_US
dc.relation.ispartofTURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCESen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectSupport vector machinesen_US
dc.subjectbone ageen_US
dc.subjectcomputer-aided diagnosisen_US
dc.subjectimage analysesen_US
dc.subjectfeature rankingen_US
dc.titleBone age determination in young children (newborn to 6 years old) using support vector machinesen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu