An Examination of Temporomandibular Joint Disc Displacement through Magnetic Resonance Imaging by Integrating Artificial Intelligence: Preliminary Findings

被引:0
作者
Almasan, Oana [1 ]
Muresanu, Sorana [2 ]
Hedesiu, Petra [3 ]
Cotor, Andrei [4 ]
Baciut, Mihaela [2 ]
Roman, Raluca [2 ]
机构
[1] Iuliu Hatieganu Univ Med & Pharm, Dept Prosthet Dent & Dent Mat, Cluj Napoca 400006, Romania
[2] Iuliu Hatieganu Univ Med & Pharm, Dept Maxillofacial Surg & Implantol, 37 Iuliu Hossu St, Cluj Napoca 400029, Romania
[3] Emil Racovi?a Coll, 9-11 Mihail Kogalniceanu, Cluj Napoca 400084, Romania
[4] Babes Bolyai Univ, Comp Sci Dept, 1 Mihail Kogalniceanu, Cluj Napoca 400084, Romania
来源
MEDICINA-LITHUANIA | 2024年 / 60卷 / 09期
关键词
temporomandibular joint; disc displacement; artificial intelligence; deep learning; magnetic resonance imaging; RECOMMENDATIONS;
D O I
10.3390/medicina60091396
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background and Objectives: This research was aimed at constructing a complete automated temporomandibular joint disc position identification system that could assist with magnetic resonance imaging disc displacement diagnosis on oblique sagittal and oblique coronal images. Materials and Methods: The study included fifty subjects with magnetic resonance imaging scans of the temporomandibular joint. Oblique sagittal and coronal sections of the magnetic resonance imaging scans were analyzed. Investigations were performed on the right and left coronal images with a closed mouth, as well as right and left sagittal images with closed and open mouths. Three hundred sagittal and coronal images were employed to train the artificial intelligence algorithm. Results: The accuracy ratio of the completely computerized articular disc identification method was 81%. Conclusions: An automated and accurate evaluation of temporomandibular joint disc position was developed by using both oblique sagittal and oblique coronal magnetic resonance imaging images.
引用
收藏
页数:10
相关论文
共 39 条
  • [1] Petrotympanic Fissure Architecture and Malleus Location in Temporomandibular Joint Disorders
    Almasan, Oana
    Leucuta, Daniel-Corneliu
    Dinu, Cristian
    Buduru, Smaranda
    Baciut, Mihaela
    Hedesiu, Mihaela
    [J]. TOMOGRAPHY, 2022, 8 (05) : 2460 - 2470
  • [2] Cadar Mihai, 2024, Med Pharm Rep, V97, P70, DOI 10.15386/mpr-2548
  • [3] Relationship Between Temporomandibular Joint Effusion, Pain, and Jaw Function Limitation: A 2D and 3D Comparative Study
    Han, Sophie Lau Rui
    Xiang, Jie
    Zeng, Xiang-Xiang
    Fan, Pei-Di
    Cheng, Qiao-Yu
    Zhou, Xue-Man
    Ye, Zheng
    Xiong, Xin
    Wang, Jun
    [J]. JOURNAL OF PAIN RESEARCH, 2024, 17 : 2051 - 2062
  • [4] ImageNet, About us
  • [5] Automated segmentation of articular disc of the temporomandibular joint on magnetic resonance images using deep learning
    Ito, Shota
    Mine, Yuichi
    Yoshimi, Yuki
    Takeda, Saori
    Tanaka, Akari
    Onishi, Azusa
    Peng, Tzu-Yu
    Nakamoto, Takashi
    Nagasaki, Toshikazu
    Kakimoto, Naoya
    Murayama, Takeshi
    Tanimoto, Kotaro
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [6] Diagnosis of temporomandibular disorders using artificial intelligence technologies: A systematic review and meta-analysis
    Jha, Nayansi
    Lee, Kwang-Sig
    Kim, Yoon-Ji
    [J]. PLOS ONE, 2022, 17 (08):
  • [7] Classifying Temporomandibular Disorder with Artificial Intelligent Architecture Using Magnetic Resonance Imaging
    Kao, Zih-Kai
    Chiu, Neng-Tai
    Wu, Hung-Ta Hondar
    Chang, Wan-Chen
    Wang, Ding-Han
    Kung, Yen-Ying
    Tu, Pei-Chi
    Lo, Wen-Liang
    Wu, Yu-Te
    [J]. ANNALS OF BIOMEDICAL ENGINEERING, 2023, 51 (03) : 517 - 526
  • [8] Ke Dong, 2020, 2020 2nd International Conference on Information Technology and Computer Application (ITCA), P476, DOI 10.1109/ITCA52113.2020.00106
  • [9] Using deep learning to predict temporomandibular joint disc perforation based on magnetic resonance imaging
    Kim, Jae-Young
    Kim, Dongwook
    Jeon, Kug Jin
    Kim, Hwiyoung
    Huh, Jong-Ki
    [J]. SCIENTIFIC REPORTS, 2021, 11 (01)
  • [10] A novel artificial neural network for the diagnosis of orofacial pain and temporomandibular disorders
    Kreiner, Marcelo
    Viloria, Jesus
    [J]. JOURNAL OF ORAL REHABILITATION, 2022, 49 (09) : 884 - 889