摘要：

牙结石是导致牙周病的重要致病因素之一，其精准识别对牙周病的防治至关重要。传统牙结石识别方法存在主观性强、准确性低的问题，尤其难以检测龈下隐蔽部位的结石，难以满足现代临床需求。近年来，光学检测技术因其非侵入性和高灵敏度等特点受到广泛关注。多种光学技术为牙结石识别提供了新的思路，如偏振光检测、光学相干断层扫描（optical coherence tomography，OCT）、差示反射法（differential reflectometry）、高光谱成像（hyperspectral imaging，HSI）和荧光光谱系统等。同时，人工智能（artificial intelligence，AI）技术，特别是机器学习和深度学习与光学技术的结合，显著提高了牙结石识别的自动化和智能化程度。本文综述了目前主流的牙结石识别方法，对比分析了各种技术的优缺点，并对未来发展方向进行了展望，旨在为牙结石识别的研究和临床应用提供参考。

Abstract:

Dental calculus is a significant contributor to periodontal disease, making its accurate identification crucial for effective prevention and treatment. Traditional methods for identifying dental calculus have the problems of strong subjectivity and low accuracy, especially when it comes to detecting calculus in the concealed subgingival areas, which cannot meet the demands of modern clinical practice. Recently, optical detection technology has attracted widespread attention due to its non-invasive and high-sensitivity characteristics. A variety of optical techniques have provided new ideas for the identification of dental calculus, such as polarization detection, optical coherence tomography (OCT), differential reflectometry, hyperspectral imaging (HSI), and fluorescence spectroscopy systems. Furthermore, artificial intelligence (AI) technology, particularly the combination of machine learning and deep learning with optical techniques, has significantly enhanced the level of automation and intelligence in the identification of dental calculus. This review provides the current mainstream methods for identifying dental calculus, compares and analyzes the advantages and disadvantages of each technology, and looks forward to the future development direction. This work aims to guide research and clinical application of dental calculus detection technologies.

中图分类号: 

• 牙结石

• 光学成像

• 人工智能

• 牙周病诊断

• dental calculus

• optical imaging

• artificial intelligence

• periodontal diagnosis