IVCVAug 31, 2023

Object Detection for Caries or Pit and Fissure Sealing Requirement in Children's First Permanent Molars

arXiv:2308.16551v13 citationsh-index: 9
Originality Synthesis-oriented
AI Analysis

This addresses the issue of timely detection for children's dental health, which is currently reliant on experienced dentists, by enabling in-home screening through a mobile app, though it is incremental as it applies existing object detection models to a new medical domain.

The paper tackles the problem of detecting dental caries and pit and fissure sealing requirements in children's first permanent molars by developing an automated method using oral photos from smartphones, achieving a best mAP of 72.3 with the YOLOXs model and a tiling strategy.

Dental caries is one of the most common oral diseases that, if left untreated, can lead to a variety of oral problems. It mainly occurs inside the pits and fissures on the occlusal/buccal/palatal surfaces of molars and children are a high-risk group for pit and fissure caries in permanent molars. Pit and fissure sealing is one of the most effective methods that is widely used in prevention of pit and fissure caries. However, current detection of pits and fissures or caries depends primarily on the experienced dentists, which ordinary parents do not have, and children may miss the remedial treatment without timely detection. To address this issue, we present a method to autodetect caries and pit and fissure sealing requirements using oral photos taken by smartphones. We use the YOLOv5 and YOLOX models and adopt a tiling strategy to reduce information loss during image pre-processing. The best result for YOLOXs model with tiling strategy is 72.3 mAP.5, while the best result without tiling strategy is 71.2. YOLOv5s6 model with/without tiling attains 70.9/67.9 mAP.5, respectively. We deploy the pre-trained network to mobile devices as a WeChat applet, allowing in-home detection by parents or children guardian.

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