Abstract
Dental panoramic radiography (DPR) is a method commonly used in dentistry for patient diagnosis. This study presents a new technique that combines a regional convolutional neural network (RCNN), Single Shot Multibox Detector, and heuristic methods to detect and number the teeth and implants with only fixtures in a DPR image. This technology is highly significant in providing statistical information and personal identification based on DPR and separating the images of individual teeth, which serve as basic data for various DPR-based AI algorithms. As a result, the mAP(@IOU = 0.5) of the tooth, implant fixture, and crown detection using the RCNN algorithm were obtained at rates of 96.7%, 45.1%, and 60.9%, respectively. Further, the sensitivity, specificity, and accuracy of the tooth numbering algorithm using a convolutional neural network and heuristics were 84.2%, 75.5%, and 84.5%, respectively. Techniques to analyze DPR images, including implants and bridges, were developed, enabling the possibility of applying AI to orthodontic or implant DPR images of patients.
Highlights
Dental panoramic radiography (DPR) is an examination that uses an extremely small dose of ionizing radiation to capture a single image of the entire mouth
The performance of the dental object detection model was evaluated based on the standards of the intersection over union (IOU)
We presented an algorithm that can detect dental objects in a DPR image and assign a number to each tooth based on its shape and location as obtained using the regional convolutional neural network (RCNN) and convolutional neural network (CNN) algorithms
Summary
Dental panoramic radiography (DPR) is an examination that uses an extremely small dose of ionizing radiation to capture a single image of the entire mouth. This technique is commonly applied by dentists and oral surgeons in their everyday practice and has significant potential in the planning of treatment involving dentures, braces, extractions, and implants. DPR is a commonly used imaging method applied to an overall evaluation of the jaw bones and teeth. Several attempts to aid in the diagnosis by an automatic reading of panoramic images have remained at the early stage of development owing to problems such as diagnostic accuracy [2]
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