Diş problemleri tanısı için derin ögrenme tabanlı çoklu-hastalık tespiti

Abstract

This work uses deep learning to automatically classify a set of dental pathologies from wide-field dental X-rays named panoramic radiographs. 9,573 adult and child patients' X-ray images form our dataset, each of which is manually annotated to 19 different dental pathologies. The proposed method leverages advanced deep learning models to diagnose a set of oral diseases and achieves state-of-the-art results. YOLO and DETR models are compared for their dental problem detection and classification accuracy. This complete AI-based method produces quick and ac-curate diagnoses of oral health, which allows dental practitioners to provide more informed decisions quickly and reliably. With evidence-based interpretation of AI results, we believe that the proposed method is a sensible way of supplementing dentists' diagnoses