深度学习算法及其在牙科x光片分析中的应用综述

Suvarna Bhat, Gajanan K. Birajdar, Mukesh D. Patil
{"title":"深度学习算法及其在牙科x光片分析中的应用综述","authors":"Suvarna Bhat,&nbsp;Gajanan K. Birajdar,&nbsp;Mukesh D. Patil","doi":"10.1016/j.health.2023.100282","DOIUrl":null,"url":null,"abstract":"<div><p>The Integration of machine learning and traditional image processing in dentistry has resulted in many applications like automatic teeth identification and numbering, caries, anomaly, disease detection, and dental treatment prediction. They have a broad scope in different applications observed in the dentistry literature review. This study reviews the literature on deep learning and dental radiograph analysis. We present an overview of machine learning algorithms in different areas of dentistry: tooth identification and numbering, Dental disease detection, and dental predictive treatment models. The methods under each area are briefly discussed. The dental radiograph data set required for performing experiments is summarized from the available literature. The study concludes by discussing new research opportunities and initiatives in this field. This paper offers a comprehensive overview of this innovative, challenging, and growing area in dentistry.</p></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772442523001491/pdfft?md5=5341805f4bffb717b9e0804dba034f1a&pid=1-s2.0-S2772442523001491-main.pdf","citationCount":"0","resultStr":"{\"title\":\"A comprehensive survey of deep learning algorithms and applications in dental radiograph analysis\",\"authors\":\"Suvarna Bhat,&nbsp;Gajanan K. Birajdar,&nbsp;Mukesh D. Patil\",\"doi\":\"10.1016/j.health.2023.100282\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The Integration of machine learning and traditional image processing in dentistry has resulted in many applications like automatic teeth identification and numbering, caries, anomaly, disease detection, and dental treatment prediction. They have a broad scope in different applications observed in the dentistry literature review. This study reviews the literature on deep learning and dental radiograph analysis. We present an overview of machine learning algorithms in different areas of dentistry: tooth identification and numbering, Dental disease detection, and dental predictive treatment models. The methods under each area are briefly discussed. The dental radiograph data set required for performing experiments is summarized from the available literature. The study concludes by discussing new research opportunities and initiatives in this field. This paper offers a comprehensive overview of this innovative, challenging, and growing area in dentistry.</p></div>\",\"PeriodicalId\":73222,\"journal\":{\"name\":\"Healthcare analytics (New York, N.Y.)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772442523001491/pdfft?md5=5341805f4bffb717b9e0804dba034f1a&pid=1-s2.0-S2772442523001491-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Healthcare analytics (New York, N.Y.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772442523001491\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare analytics (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772442523001491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

机器学习和传统图像处理在牙科领域的集成已经产生了许多应用,如自动牙齿识别和编号,龋齿,异常,疾病检测和牙科治疗预测。在牙科文献综述中观察到,它们在不同的应用中具有广泛的范围。本研究回顾了深度学习和牙科x光片分析的文献。我们介绍了机器学习算法在牙科不同领域的概述:牙齿识别和编号,牙科疾病检测和牙科预测治疗模型。简要讨论了各个领域的方法。从现有文献中总结了进行实验所需的牙科x光片数据集。研究最后讨论了该领域的新研究机会和举措。本文提供了一个全面的概述,这一创新,具有挑战性,并在牙科领域不断发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comprehensive survey of deep learning algorithms and applications in dental radiograph analysis

The Integration of machine learning and traditional image processing in dentistry has resulted in many applications like automatic teeth identification and numbering, caries, anomaly, disease detection, and dental treatment prediction. They have a broad scope in different applications observed in the dentistry literature review. This study reviews the literature on deep learning and dental radiograph analysis. We present an overview of machine learning algorithms in different areas of dentistry: tooth identification and numbering, Dental disease detection, and dental predictive treatment models. The methods under each area are briefly discussed. The dental radiograph data set required for performing experiments is summarized from the available literature. The study concludes by discussing new research opportunities and initiatives in this field. This paper offers a comprehensive overview of this innovative, challenging, and growing area in dentistry.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Healthcare analytics (New York, N.Y.)
Healthcare analytics (New York, N.Y.) Applied Mathematics, Modelling and Simulation, Nursing and Health Professions (General)
CiteScore
4.40
自引率
0.00%
发文量
0
审稿时长
79 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信