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

被引:0
|
作者
Kadan, E. A. [1 ]
Kilic, R. [2 ]
Miloglu, O. [1 ]
Ozbek, I. Y. [3 ]
Oral, E. A. [2 ]
机构
[1] Ataturk Univ, Fac Dent, Dept Oral Dent & Maxillofacial Radiol, TR-25240 Erzurum, Turkiye
[2] Ataturk Univ, Fac Engn, Dept Elect Elect Engn, Erzurum, Turkiye
[3] Ataturk Univ, High Performance Comp Applicat & Res Ctr, Dept Elect Elect Engn, Erzurum, Turkiye
关键词
Artificial intelligence; deep learning; machine learning; maxillary molars; maxillary sinus; neural networks; 3RD MOLARS; FLOOR; DISTANCES; SINUSITIS; POSITION; ANATOMY; APICES;
D O I
10.4103/njcp.njcp_220_24
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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.
引用
收藏
页码:669 / 677
页数:9
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