Neil Abraham Barnes , S Sharath , Winniecia Dkhar , Yogesh Chhaparwal , Kaushik Nayak
{"title":"用半自动和全自动方法对下颌管进行 CBCT 分段：系统性综述","authors":"Neil Abraham Barnes , S Sharath , Winniecia Dkhar , Yogesh Chhaparwal , Kaushik Nayak","doi":"10.1016/j.cegh.2024.101760","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>The application of AI algorithms for the detection of the mandibular canal in Cone Beam Computed Tomography (CBCT) holds immense promise in dentistry.</p></div><div><h3>Aim</h3><p>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.</p></div>","PeriodicalId":46404,"journal":{"name":"Clinical Epidemiology and Global Health","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2213398424002574/pdfft?md5=16a7fb66e23c0da9a2228af4d05a41d5&pid=1-s2.0-S2213398424002574-main.pdf","citationCount":"0","resultStr":"{\"title\":\"CBCT segmentation of the mandibular canal with both semi-automated and fully automated methods: A systematic review\",\"authors\":\"Neil Abraham Barnes , S Sharath , Winniecia Dkhar , Yogesh Chhaparwal , Kaushik Nayak\",\"doi\":\"10.1016/j.cegh.2024.101760\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>The application of AI algorithms for the detection of the mandibular canal in Cone Beam Computed Tomography (CBCT) holds immense promise in dentistry.</p></div><div><h3>Aim</h3><p>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.</p></div>\",\"PeriodicalId\":46404,\"journal\":{\"name\":\"Clinical Epidemiology and Global Health\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2213398424002574/pdfft?md5=16a7fb66e23c0da9a2228af4d05a41d5&pid=1-s2.0-S2213398424002574-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Epidemiology and Global Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2213398424002574\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Epidemiology and Global Health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213398424002574","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
CBCT segmentation of the mandibular canal with both semi-automated and fully automated methods: A systematic review
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.
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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