Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method
Objective: Before dental procedures, hand-wrist radiographs are used to plan treatment time and determine skeletal maturity. This study aims to determine gender from hand-wrist radiographs using different deep-learning methods.Methods: The left hand-wrist radiographs of 1044 individuals (534 males a...
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| Format: | Article |
| Language: | English |
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Atatürk University
2025-01-01
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| Series: | Current Research in Dental Sciences |
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| Online Access: | https://dergipark.org.tr/tr/download/article-file/4516648 |
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| author | İbrahim Yücel Özbek Mustafa Taha Güller Zeynep Turanli Tosun Nida Kumbasar Özkan Miloğlu |
| author_facet | İbrahim Yücel Özbek Mustafa Taha Güller Zeynep Turanli Tosun Nida Kumbasar Özkan Miloğlu |
| author_sort | İbrahim Yücel Özbek |
| collection | DOAJ |
| description | Objective: Before dental procedures, hand-wrist radiographs are used to plan treatment time and determine skeletal maturity. This study aims to determine gender from hand-wrist radiographs using different deep-learning methods.Methods: The left hand-wrist radiographs of 1044 individuals (534 males and 510 females) were pre-processed to clarify the image and adjust the contrast. In the gender classification problem, AlexNet, VGG16 and VGG19 transfer learning methods were both used as separate classifiers, and the features taken from these methods were combined and given to the support vector machine (SVM) classifier.Results: The results revealed that image analysis and deep learning techniques provided 91.1% accuracy in gender determination.Conclusion: Hand-wrist radiographs exhibited sexual dimorphism and could be used in gender prediction.Keywords: Deep learning; İmage analysis; Hand-wrist radiographs; Gender determination |
| format | Article |
| id | doaj-art-db8043e5936f4236a37893f65768e58c |
| institution | Kabale University |
| issn | 2822-2555 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Atatürk University |
| record_format | Article |
| series | Current Research in Dental Sciences |
| spelling | doaj-art-db8043e5936f4236a37893f65768e58c2025-02-03T10:38:09ZengAtatürk UniversityCurrent Research in Dental Sciences2822-25552025-01-013512710.17567/currresdentsci.161886055Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Methodİbrahim Yücel Özbek0Mustafa Taha Güller1Zeynep Turanli Tosun2Nida Kumbasar3Özkan Miloğlu4ERZURUM TECHNICAL UNIVERSITY, INSTITUTE OF SCIENCE, ELECTRICAL AND ELECTRONIC ENGINEERINGGİRESUN ÜNİVERSİTESİ, DİŞ HEKİMLİĞİ FAKÜLTESİ, KLİNİK BİLİMLER BÖLÜMÜ, AĞIZ, DİŞ VE ÇENE RADYOLOJİSİ ANABİLİM DALIATATÜRK ÜNİVERSİTESİ, DİŞ HEKİMLİĞİ FAKÜLTESİ, KLİNİK BİLİMLER BÖLÜMÜ, AĞIZ DİŞ VE ÇENE RADYOLOJİSİ ANABİLİM DALIKOCAELI UNIVERSITY, INFORMATICS TECHNOLOGIES APPLICATION AND RESEARCH CENTERDİCLE ÜNİVERSİTESİ, DİŞ HEKİMLİĞİ FAKÜLTESİ, KLİNİK BİLİMLER BÖLÜMÜ, AĞIZ, DİŞ, ÇENE RADYOLOJİSİ ANABİLİM DALIObjective: Before dental procedures, hand-wrist radiographs are used to plan treatment time and determine skeletal maturity. This study aims to determine gender from hand-wrist radiographs using different deep-learning methods.Methods: The left hand-wrist radiographs of 1044 individuals (534 males and 510 females) were pre-processed to clarify the image and adjust the contrast. In the gender classification problem, AlexNet, VGG16 and VGG19 transfer learning methods were both used as separate classifiers, and the features taken from these methods were combined and given to the support vector machine (SVM) classifier.Results: The results revealed that image analysis and deep learning techniques provided 91.1% accuracy in gender determination.Conclusion: Hand-wrist radiographs exhibited sexual dimorphism and could be used in gender prediction.Keywords: Deep learning; İmage analysis; Hand-wrist radiographs; Gender determinationhttps://dergipark.org.tr/tr/download/article-file/4516648deep learningimage analysis; hand-wrist radiographs |
| spellingShingle | İbrahim Yücel Özbek Mustafa Taha Güller Zeynep Turanli Tosun Nida Kumbasar Özkan Miloğlu Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method Current Research in Dental Sciences deep learning image analysis ; hand-wrist radiographs |
| title | Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method |
| title_full | Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method |
| title_fullStr | Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method |
| title_full_unstemmed | Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method |
| title_short | Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method |
| title_sort | gender classification with hand wrist radiographs using the deep learning method |
| topic | deep learning image analysis ; hand-wrist radiographs |
| url | https://dergipark.org.tr/tr/download/article-file/4516648 |
| work_keys_str_mv | AT ibrahimyucelozbek genderclassificationwithhandwristradiographsusingthedeeplearningmethod AT mustafatahaguller genderclassificationwithhandwristradiographsusingthedeeplearningmethod AT zeynepturanlitosun genderclassificationwithhandwristradiographsusingthedeeplearningmethod AT nidakumbasar genderclassificationwithhandwristradiographsusingthedeeplearningmethod AT ozkanmiloglu genderclassificationwithhandwristradiographsusingthedeeplearningmethod |