A DEEP-LEARNING MODEL FOR IDIOPATHIC OSTEOSCLEROSIS DETECTION ON PANORAMIC RADIOGRAPHS

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Yesiltepe S., Bayrakdar İ. Ş., Orhan K., Çelik Ö., Bilgir E., Aslan A. F., ...Daha Fazla

MEDICAL PRINCIPLES AND PRACTICE, cilt.31, ss.555-561, 2022 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 31
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1159/000527145
  • Dergi Adı: MEDICAL PRINCIPLES AND PRACTICE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CINAHL, EMBASE, MEDLINE, Directory of Open Access Journals
  • Sayfa Sayıları: ss.555-561
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

Objective: The purpose of the study is to create artificial intelligence (AI) system in detecting idiopathic osteosclerosis (IO) on panoramic radiographs for automatic, routine, and simple evaluations. Subject and Methods: In this study, a deep learning method was carried out with panoramic radiographs obtained from healthy patients. A total of 493 anonymized panoramic radiographs were used to develop the AI system (XXXXX, XXXXX-XXXXXX) for the detection of IOs. The panoramic radiographs were acquired from the radiology archives of the Department of Oral and Maxillofacial Radiology of the Faculty of Dentistry of XXXXXX University. GoogleNet Inception V2 model implemented with TensorFlow library was used for the detection of IOs. Confusion matrix was used to predict model achievements.Results: 50 IOs were detected accurately by the AI model from the 52 test images which had 57 IOs. The sensitivity, precision, and F-measure values were 0.88, 0.83, and 0.86, respectively. Conclusion: Deep learning-based AI algorithm have the potential to detect IOs accurately on panoramic radiographs. AI systems may reduce of dentist diagnostic efforts in the future.