158 related articles for article (PubMed ID: 33758266)
1. Using deep learning to predict temporomandibular joint disc perforation based on magnetic resonance imaging.
Kim JY; Kim D; Jeon KJ; Kim H; Huh JK
Sci Rep; 2021 Mar; 11(1):6680. PubMed ID: 33758266
[TBL] [Abstract][Full Text] [Related]
2. Automatic detection of anteriorly displaced temporomandibular joint discs on magnetic resonance images using a deep learning algorithm.
Lin B; Cheng M; Wang S; Li F; Zhou Q
Dentomaxillofac Radiol; 2022 Mar; 51(3):20210341. PubMed ID: 34788124
[TBL] [Abstract][Full Text] [Related]
3. Temporomandibular joint segmentation in MRI images using deep learning.
Li M; Punithakumar K; Major PW; Le LH; Nguyen KT; Pacheco-Pereira C; Kaipatur NR; Nebbe B; Jaremko JL; Almeida FT
J Dent; 2022 Dec; 127():104345. PubMed ID: 36368120
[TBL] [Abstract][Full Text] [Related]
4. Explainable deep learning-based clinical decision support engine for MRI-based automated diagnosis of temporomandibular joint anterior disk displacement.
Yoon K; Kim JY; Kim SJ; Huh JK; Kim JW; Choi J
Comput Methods Programs Biomed; 2023 May; 233():107465. PubMed ID: 36933315
[TBL] [Abstract][Full Text] [Related]
5. Magnetic resonance imaging applied to the diagnosis of perforation of the temporomandibular joint.
Shen P; Huo L; Zhang SY; Yang C; Cai XY; Liu XM
J Craniomaxillofac Surg; 2014 Sep; 42(6):874-8. PubMed ID: 24530082
[TBL] [Abstract][Full Text] [Related]
6. Advantages of deep learning with convolutional neural network in detecting disc displacement of the temporomandibular joint in magnetic resonance imaging.
Lee YH; Won JH; Kim S; Auh QS; Noh YK
Sci Rep; 2022 Jul; 12(1):11352. PubMed ID: 35790841
[TBL] [Abstract][Full Text] [Related]
7. A nomogram for classification of temporomandibular joint disk perforation based on magnetic resonance imaging.
Kim JY; Jeon KJ; Kim MG; Park KH; Huh JK
Oral Surg Oral Med Oral Pathol Oral Radiol; 2018 Jun; 125(6):682-692. PubMed ID: 29574057
[TBL] [Abstract][Full Text] [Related]
8. Automated segmentation of articular disc of the temporomandibular joint on magnetic resonance images using deep learning.
Ito S; Mine Y; Yoshimi Y; Takeda S; Tanaka A; Onishi A; Peng TY; Nakamoto T; Nagasaki T; Kakimoto N; Murayama T; Tanimoto K
Sci Rep; 2022 Jan; 12(1):221. PubMed ID: 34997167
[TBL] [Abstract][Full Text] [Related]
9. Early diagnosis of degenerative changes in the articular/fibrocartilaginous disc of the temporomandibular joint in patients with temporomandibular disorders using delayed gadolinium-enhanced MRI at 3 Tesla - preliminary results.
Eder J; Szomolanyi P; Schmid-Schwap M; Bristela M; Skolka A; Pittschieler E; Piehslinger E; Trattnig S
Magn Reson Imaging; 2020 Apr; 67():24-27. PubMed ID: 31843417
[TBL] [Abstract][Full Text] [Related]
10. Automatic segmentation of the temporomandibular joint disc on magnetic resonance images using a deep learning technique.
Nozawa M; Ito H; Ariji Y; Fukuda M; Igarashi C; Nishiyama M; Ogi N; Katsumata A; Kobayashi K; Ariji E
Dentomaxillofac Radiol; 2022 Jan; 51(1):20210185. PubMed ID: 34347537
[TBL] [Abstract][Full Text] [Related]
11. In vivo prediction of temporomandibular joint disc thickness and position changes for different jaw positions.
Sagl B; Schmid-Schwap M; Piehslinger E; Kronnerwetter C; Kundi M; Trattnig S; Stavness I
J Anat; 2019 May; 234(5):718-727. PubMed ID: 30786005
[TBL] [Abstract][Full Text] [Related]
12. Diagnostic accuracy of fat-saturated T2-weighted magnetic resonance imaging in the diagnosis of perforation of the articular disc of the temporomandibular joint.
Yura S; Nobata K; Shima T
Br J Oral Maxillofac Surg; 2012 Jun; 50(4):365-8. PubMed ID: 21723011
[TBL] [Abstract][Full Text] [Related]
13. Correlation between the disc status in MRI and the different types of traumatic temporomandibular joint ankylosis.
Zheng JS; Jiao ZX; Zhang SY; Yang C; Abdelrehem A; Chen MJ; He DM; Dong MJ
Dentomaxillofac Radiol; 2015; 44(4):20140201. PubMed ID: 25564884
[TBL] [Abstract][Full Text] [Related]
14. Predicting Inpatient Payments Prior to Lower Extremity Arthroplasty Using Deep Learning: Which Model Architecture Is Best?
Karnuta JM; Navarro SM; Haeberle HS; Helm JM; Kamath AF; Schaffer JL; Krebs VE; Ramkumar PN
J Arthroplasty; 2019 Oct; 34(10):2235-2241.e1. PubMed ID: 31230954
[TBL] [Abstract][Full Text] [Related]
15. Development and Validation of a Magnetic Resonance Imaging-Based Machine Learning Model for TMJ Pathologies.
Orhan K; Driesen L; Shujaat S; Jacobs R; Chai X
Biomed Res Int; 2021; 2021():6656773. PubMed ID: 34327235
[TBL] [Abstract][Full Text] [Related]
16. Ultrasonographic evaluation of disc displacement of the temporomandibular joint compared with magnetic resonance imaging.
Cakir-Ozkan N; Sarikaya B; Erkorkmaz U; Aktürk Y
J Oral Maxillofac Surg; 2010 May; 68(5):1075-80. PubMed ID: 20189702
[TBL] [Abstract][Full Text] [Related]
17. Ultrasound assessment of increased capsular width as a predictor of temporomandibular joint effusion.
Manfredini D; Tognini F; Melchiorre D; Zampa V; Bosco M
Dentomaxillofac Radiol; 2003 Nov; 32(6):359-64. PubMed ID: 15070837
[TBL] [Abstract][Full Text] [Related]
18. Temporomandibular joint (TMJ) pain revisited with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).
Tasali N; Cubuk R; Aricak M; Ozarar M; Saydam B; Nur H; Tuncbilek N
Eur J Radiol; 2012 Mar; 81(3):603-8. PubMed ID: 21300493
[TBL] [Abstract][Full Text] [Related]
19. [A preliminary study on the registration of MRI and cone beam CT images of temporomandibular joint disc].
He YM; Wang HY; Feng YP; Li HM; Fang W; Ke J; Long X
Zhonghua Kou Qiang Yi Xue Za Zhi; 2020 Oct; 55(10):772-777. PubMed ID: 33045790
[No Abstract] [Full Text] [Related]
20. Diagnostic efficacy of CBCT, MRI, and CBCT-MRI fused images in distinguishing articular disc calcification from loose body of temporomandibular joint.
Wang YH; Li G; Ma RH; Zhao YP; Zhang H; Meng JH; Mu CC; Sun CK; Ma XC
Clin Oral Investig; 2021 Apr; 25(4):1907-1914. PubMed ID: 32785850
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
