CBCT segmentation of the mandibular canal with both semi-automated and fully automated methods: A systematic review

IF 2.3 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Neil Abraham Barnes , S Sharath , Winniecia Dkhar , Yogesh Chhaparwal , Kaushik Nayak
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引用次数: 0

Abstract

Background

The application of AI algorithms for the detection of the mandibular canal in Cone Beam Computed Tomography (CBCT) holds immense promise in dentistry.

Aim

This review aimed to identify the semi and fully automated algorithm to localize the mandibular canal. An extensive search was conducted and, out of which 12 articles are considered for review. The result revealed using various AI algorithms achieved better accuracy in localizing the mandibular canal with reporting sensitivity and specificity above 90 %. In conclusion, it is noted that the application of AI algorithms in dentistry can provide significant benefits like improving the accuracy of reporting.

用半自动和全自动方法对下颌管进行 CBCT 分段:系统性综述
背景在锥形束计算机断层扫描(CBCT)中应用人工智能算法检测下颌管在牙科领域有着广阔的前景。我们进行了广泛的搜索,并对其中的 12 篇文章进行了审议。结果显示,使用各种人工智能算法定位下颌管的准确性更高,灵敏度和特异性均超过 90%。总之,人工智能算法在牙科中的应用可以带来显著的益处,如提高报告的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Clinical Epidemiology and Global Health
Clinical Epidemiology and Global Health PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
4.60
自引率
7.70%
发文量
218
审稿时长
66 days
期刊介绍: Clinical Epidemiology and Global Health (CEGH) is a multidisciplinary journal and it is published four times (March, June, September, December) a year. The mandate of CEGH is to promote articles on clinical epidemiology with focus on developing countries in the context of global health. We also accept articles from other countries. It publishes original research work across all disciplines of medicine and allied sciences, related to clinical epidemiology and global health. The journal publishes Original articles, Review articles, Evidence Summaries, Letters to the Editor. All articles published in CEGH are peer-reviewed and published online for immediate access and citation.
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