Guldane Magat, Ali Altındag, Fatma Pertek Hatipoglu, Omer Hatipoglu, İbrahim Sevki Bayrakdar, Ozer Celik, Kaan Orhan
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引用次数: 0
Abstract
Objectives: This study aimed to assess the effectiveness of deep convolutional neural network (CNN) algorithms for the detecting and segmentation of overhanging dental restorations in bitewing radiographs.
Methods: A total of 1160 anonymized bitewing radiographs were used to progress the artificial intelligence (AI) system for the detection and segmentation of overhanging restorations. The data were then divided into three groups: 80% for training (930 images, 2399 labels), 10% for validation (115 images, 273 labels), and 10% for testing (115 images, 306 labels). A CNN model known as You Only Look Once (YOLOv5) was trained to detect overhanging restorations in bitewing radiographs. After utilizing the remaining 115 radiographs to evaluate the efficacy of the proposed CNN model, the accuracy, sensitivity, precision, F1 score, and area under the receiver operating characteristic curve (AUC) were computed.
Results: The model demonstrated a precision of 90.9%, a sensitivity of 85.3%, and an F1 score of 88.0%. Furthermore, the model achieved an AUC of 0.859 on the receiver operating characteristic (ROC) curve. The mean average precision (mAP) at an intersection over a union (IoU) threshold of 0.5 was notably high at 0.87.
Conclusions: The findings suggest that deep CNN algorithms are highly effective in the detection and diagnosis of overhanging dental restorations in bitewing radiographs. The high levels of precision, sensitivity, and F1 score, along with the significant AUC and mAP values, underscore the potential of these advanced deep learning techniques in revolutionizing dental diagnostic procedures.
期刊介绍:
Dentomaxillofacial Radiology (DMFR) is the journal of the International Association of Dentomaxillofacial Radiology (IADMFR) and covers the closely related fields of oral radiology and head and neck imaging.
Established in 1972, DMFR is a key resource keeping dentists, radiologists and clinicians and scientists with an interest in Head and Neck imaging abreast of important research and developments in oral and maxillofacial radiology.
The DMFR editorial board features a panel of international experts including Editor-in-Chief Professor Ralf Schulze. Our editorial board provide their expertise and guidance in shaping the content and direction of the journal.
Quick Facts:
- 2015 Impact Factor - 1.919
- Receipt to first decision - average of 3 weeks
- Acceptance to online publication - average of 3 weeks
- Open access option
- ISSN: 0250-832X
- eISSN: 1476-542X