E A Kadan, R Kiliç, Ö Miloğlu, İ Y Özbek, E A Oral
{"title":"利用深度学习模型评估上颌臼齿和上颌窦的关系的全景放射摄影,改进了锥形束计算机断层扫描的结果。","authors":"E A Kadan, R Kiliç, Ö Miloğlu, İ Y Özbek, E A Oral","doi":"10.4103/njcp.njcp_220_24","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Panoramic radiography (PR) is available to determine the contact relationship between maxillary molar teeth (MMT) and the maxillary sinus floor (MSF). However, as PRs do not provide clear and detailed anatomical information, advanced imaging methods can be used.</p><p><strong>Aim: </strong>The aim of this study was to evaluate the diagnostic performance of deep learning (DL) applications that assess the relationship of the MSF to the first maxillary molar teeth (fMMT) and second maxillary molar teeth (sMMT) on PRs with data confirmed by cone beam computed tomography (CBCT).</p><p><strong>Methods: </strong>A total of 2162 fMMT and sMMT were included in this retrospective study. The contact relationship of teeth with MSF was compared among DL methods.</p><p><strong>Results: </strong>DL methods, such as GoogLeNet, VGG16, VGG19, DarkNet19, and DarkNet53, were used to evaluate the contact relationship between MMT and MSF, and 85.89% accuracy was achieved by majority voting. In addition, 88.72%, 81.19%, 89.39%, and 83.14% accuracy rates were obtained in right fMMT, right sMMT, left fMMT, and left sMMT, respectively.</p><p><strong>Conclusion: </strong>DL models showed high accuracy values in detecting the relationship of fMMT and sMMT with MSF.</p>","PeriodicalId":19431,"journal":{"name":"Nigerian Journal of Clinical Practice","volume":"27 5","pages":"669-677"},"PeriodicalIF":0.7000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Panoramic Radiography in the Evaluation of the Relationship of Maxillary Molar Teeth and Maxillary Sinuses on the Deep Learning Models Improved with the Findings Obtained by Cone Beam Computed Tomography.\",\"authors\":\"E A Kadan, R Kiliç, Ö Miloğlu, İ Y Özbek, E A Oral\",\"doi\":\"10.4103/njcp.njcp_220_24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Panoramic radiography (PR) is available to determine the contact relationship between maxillary molar teeth (MMT) and the maxillary sinus floor (MSF). However, as PRs do not provide clear and detailed anatomical information, advanced imaging methods can be used.</p><p><strong>Aim: </strong>The aim of this study was to evaluate the diagnostic performance of deep learning (DL) applications that assess the relationship of the MSF to the first maxillary molar teeth (fMMT) and second maxillary molar teeth (sMMT) on PRs with data confirmed by cone beam computed tomography (CBCT).</p><p><strong>Methods: </strong>A total of 2162 fMMT and sMMT were included in this retrospective study. The contact relationship of teeth with MSF was compared among DL methods.</p><p><strong>Results: </strong>DL methods, such as GoogLeNet, VGG16, VGG19, DarkNet19, and DarkNet53, were used to evaluate the contact relationship between MMT and MSF, and 85.89% accuracy was achieved by majority voting. In addition, 88.72%, 81.19%, 89.39%, and 83.14% accuracy rates were obtained in right fMMT, right sMMT, left fMMT, and left sMMT, respectively.</p><p><strong>Conclusion: </strong>DL models showed high accuracy values in detecting the relationship of fMMT and sMMT with MSF.</p>\",\"PeriodicalId\":19431,\"journal\":{\"name\":\"Nigerian Journal of Clinical Practice\",\"volume\":\"27 5\",\"pages\":\"669-677\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nigerian Journal of Clinical Practice\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.4103/njcp.njcp_220_24\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/5/29 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nigerian Journal of Clinical Practice","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4103/njcp.njcp_220_24","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/29 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Panoramic Radiography in the Evaluation of the Relationship of Maxillary Molar Teeth and Maxillary Sinuses on the Deep Learning Models Improved with the Findings Obtained by Cone Beam Computed Tomography.
Background: Panoramic radiography (PR) is available to determine the contact relationship between maxillary molar teeth (MMT) and the maxillary sinus floor (MSF). However, as PRs do not provide clear and detailed anatomical information, advanced imaging methods can be used.
Aim: The aim of this study was to evaluate the diagnostic performance of deep learning (DL) applications that assess the relationship of the MSF to the first maxillary molar teeth (fMMT) and second maxillary molar teeth (sMMT) on PRs with data confirmed by cone beam computed tomography (CBCT).
Methods: A total of 2162 fMMT and sMMT were included in this retrospective study. The contact relationship of teeth with MSF was compared among DL methods.
Results: DL methods, such as GoogLeNet, VGG16, VGG19, DarkNet19, and DarkNet53, were used to evaluate the contact relationship between MMT and MSF, and 85.89% accuracy was achieved by majority voting. In addition, 88.72%, 81.19%, 89.39%, and 83.14% accuracy rates were obtained in right fMMT, right sMMT, left fMMT, and left sMMT, respectively.
Conclusion: DL models showed high accuracy values in detecting the relationship of fMMT and sMMT with MSF.
期刊介绍:
The Nigerian Journal of Clinical Practice is a Monthly peer-reviewed international journal published by the Medical and Dental Consultants’ Association of Nigeria. The journal’s full text is available online at www.njcponline.com. The journal allows free access (Open Access) to its contents and permits authors to self-archive final accepted version of the articles on any OAI-compliant institutional / subject-based repository. The journal makes a token charge for submission, processing and publication of manuscripts including color reproduction of photographs.