Deep Learning Based Detection of Missing Tooth Regions for Dental Implant Planning in Panoramic Radiographic Images

Dental implantation is a surgical procedure in oral and maxillofacial surgery. Detecting missing tooth regions is essential for planning dental implant placement. This study proposes an automated method that detects regions of missing teeth in panoramic radiographic images. Tooth instance segmentati...

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Bibliographic Details
Published in:Applied sciences 2022-02, Vol.12 (3), p.1595
Main Authors: Park, Jumi, Lee, Junseok, Moon, Seongyong, Lee, Kyoobin
Format: Article
Language:English
Subjects:
Automation
Chambers of commerce
Datasets
Deep learning
dental implant
dental implant placement
Dental implants
Dentistry
Image annotation
Image processing
Masks
Maxillofacial
missing tooth regions detection
Neural networks
panoramic radiographic image
Performance evaluation
Planning
Teeth
tooth instance segmentation
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Summary:Dental implantation is a surgical procedure in oral and maxillofacial surgery. Detecting missing tooth regions is essential for planning dental implant placement. This study proposes an automated method that detects regions of missing teeth in panoramic radiographic images. Tooth instance segmentation is required to accurately detect a missing tooth region in panoramic radiographic images containing obstacles, such as dental appliances or restoration. Therefore, we constructed a dataset that contains 455 panoramic radiographic images and annotations for tooth instance segmentation and missing tooth region detection. First, the segmentation model segments teeth into the panoramic radiographic image and generates teeth masks. Second, a detection model uses the teeth masks as input to predict regions of missing teeth. Finally, the detection model identifies the position and number of missing teeth in the panoramic radiographic image. We achieved 92.14% mean Average Precision (mAP) for tooth instance segmentation and 59.09% mAP for missing tooth regions detection. As a result, this method assists diagnosis by clinicians to detect missing teeth regions for implant placement.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12031595