A deep learning model using convolutional neural networks for caries detection and recognition with endoscopes.

ABSTRACT:

Background

Caries are common, especially in economically undeveloped countries with limited access to medical resources. Sometimes patient cannot even realize that they have oral problems until they feel obvious pain. Deep convolutional neural networks (CNNs) have been widely adopted for medical image analysis and management and have yielded some progress in stomatology while the endoscopes are cheap and easily used in daily life for families or other non-medical situations. Therefore, we created a deep learning model to detect and recognize caries using endoscopic images.

Methods

We used 194 images of non-caries and 1,059 images of permanent molar and premolar caries to build a classification and a segmentation model in patients of endoscope images from the Department of St

SUBMITTER: Zang X 

PROVIDER: S-EPMC9843352 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature