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Dental caries, a gradual bacterial damage to teeth, is one of the most common diseases and is still a major cause of tooth loss. It can be divided into 7 scores based on the ICDAS(International Caries Detection and Assessment System) according to the tooth condition. Early detection and treatment of dental caries can reduce the costs as well as time. As computer performance has been improved, machine learning and image processing technologies are introduced to detect and diagnose dental caries. Computer-aided Diagnosis(CADx) can assist dentists in the interpretation of several oral digital images or X-ray image. Dental caries detection system using CADx has four steps. First is image enhancement to improve the original image. Second is tooth detection which extract the tooth area from the oral structures. Third is caries detection which finds the caries lesion in tooth area. The fourth is classification which analyzes and classifies carious lesions. In this paper, we survey and introduce the various dental caries detection methods based on CADx.
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Kim et al. (2019) studied this question.
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