Bennett NG (1908) A contribution to the study of the movements of the mandible. In: Proceedings of the royal society of medicine, 1:79–98. https://doi.org/10.1177/003591570800100813

Woodford SC, Robinson DL, Mehl A, Lee PVS, Ackland DC (2020) Measurement of normal and pathological mandibular and temporomandibular joint kinematics: a systematic review. J Biomech 111:109994. https://doi.org/10.1016/j.jbiomech.2020.109994

Article  PubMed  Google Scholar 

Piehslinger E, Čelar AG, Čelar RM, Slavicek R (1991) Computerized axiography principles and methods. CRANIO® 9:344–355. https://doi.org/10.1080/08869634.1991.11678382

Article  CAS  PubMed  Google Scholar 

Wagner A, Seemann R, Schicho K, Ewers R, Piehslinger E (2003) A comparative analysis of optical and conventional axiography for the analysis of temporomandibular joint movements. J Prosthet Dent 90:503–509. https://doi.org/10.1016/S0022-3913(03)00482-7

Article  PubMed  Google Scholar 

Sójka A, Huber J, Kaczmarek E, Hędzelek W (2017) Evaluation of mandibular movement functions using instrumental ultrasound system. J Prosthodont 26:123–128. https://doi.org/10.1111/jopr.12389

Article  PubMed  Google Scholar 

Furtado DA, Pereira AA, de Andrade AO, Bellomo DP, da Silva MR (2013) A specialized motion capture system for real-time analysis of mandibular movements using infrared cameras. Biomed Eng Online 12:17. https://doi.org/10.1186/1475-925X-12-17

Article  PubMed  PubMed Central  Google Scholar 

Pinheiro A, Pereira A, Andrade A, Bellomo D Jr (2011) Measurement of jaw motion: the proposal of a simple and accurate method. J Med Eng Technol 35:125–133. https://doi.org/10.3109/03091902.2010.542270

Article  CAS  PubMed  Google Scholar 

Tian S (2020) Three-dimensional mandibular motion trajectory-tracking system based on BP neural network. Math Biosci Eng 17:5709

Article  PubMed  Google Scholar 

Peck CC, Murray GM, Johnson CWL, Klineberg IJ (1997) The variability of condylar point pathways in open-close jaw movements. J Prosthet Dent 77:394–404. https://doi.org/10.1016/S0022-3913(97)70165-3

Article  CAS  PubMed  Google Scholar 

Bapelle M, Dubromez J, Savoldelli C, Tillier Y, Ehrmann E (2021) Modjaw® device: analysis of mandibular kinematics recorded for a group of asymptomatic subjects. CRANIO® 42:1–7. https://doi.org/10.1080/08869634.2021.2000790

Article  Google Scholar 

Shu J, Ma H, Xiong X, Shao B, Zheng T, Liu Y et al (2021) Mathematical analysis of the condylar trajectories in asymptomatic subjects during mandibular motions. Med Biol Eng Comput 59:901–911. https://doi.org/10.1007/s11517-021-02346-6

Article  PubMed  Google Scholar 

Revilla-León M, Kois DE, Zeitler JM, Att W, Kois JC (2023) An overview of the digital occlusion technologies: intraoral scanners, jaw tracking systems, and computerized occlusal analysis devices. J Esthet Restor Dent 35:735–744. https://doi.org/10.1111/jerd.13044

Article  PubMed  Google Scholar 

Nagy Z, Mikolicz A, Vag J (2023) In-vitro accuracy of a novel jaw-tracking technology. J Dent 138:104730. https://doi.org/10.1016/j.jdent.2023.104730

Article  PubMed  Google Scholar 

Lassmann Ł, Nowak Z, Orthlieb J-D, Żółtowska A (2023) Complicated relationships between anterior and condylar guidance and their clinical implications—comparison by cone beam computed tomography and electronic axiography—an observational cohort cross-sectional study. Life 13:335. https://doi.org/10.3390/life13020335

Article  PubMed  PubMed Central  Google Scholar 

Zoss G, Beeler T, Gross M, Bradley D (2019) Accurate markerless jaw tracking for facial performance capture. ACM Trans Graph 38:8. https://doi.org/10.1145/3306346.3323044

Article  Google Scholar 

Hilgenberg-Sydney PB, Bonotto DV, Stechman-Neto J, Zwir LF, Pachêco-Pereira C, Canto GDL et al (2018) Diagnostic validity of CT to assess degenerative temporomandibular joint disease: a systematic review. Dentomaxillofac Radiol 47:20170389. https://doi.org/10.1259/dmfr.20170389

Article  PubMed  PubMed Central  Google Scholar 

Huang C, Xu XL, Sun YC, Guo CB (2018) A preliminary study on the three-dimensional trajectory of condyle. Zhonghua Kou Qiang Yi Xue Za Zhi 53:669–673. https://doi.org/10.3760/cma.j.issn.1002-0098.2018.10.005

Article  CAS  PubMed  Google Scholar 

Sindelar BJ, Herring SW (2005) Soft tissue mechanics of the temporomandibular joint. Cells Tissues Organs 180:36–43. https://doi.org/10.1159/000086197

Article  PubMed  Google Scholar 

Ferreira LA, Grossmann E, Januzzi E, de Paula MVQ, Carvalho ACP (2016) Diagnosis of temporomandibular joint disorders: indication of imaging exams. Braz J Otorhinolaryngol 82:341–352. https://doi.org/10.1016/j.bjorl.2015.06.010

Article  PubMed  PubMed Central  Google Scholar 

Murphy MK, MacBarb RF, Wong ME, Athanasiou KA (2013) Temporomandibular joint disorders: a review of etiology, clinical management, and tissue engineering strategies. Int J Oral Maxillofac Implants 28:e393-414

Article  PubMed  PubMed Central  Google Scholar 

Nayak KS, Lim Y, Campbell-Washburn AE, Steeden J (2022) Real-time magnetic resonance imaging. J Magn Reson Imaging 55:81–99. https://doi.org/10.1002/jmri.27411

Article  PubMed  Google Scholar 

Krohn S, Gersdorff N, Wassmann T, Merboldt K-D, Joseph AA, Buergers R et al (2016) Real-time MRI of the temporomandibular joint at 15 frames per second—a feasibility study. Eur J Radiol 85:2225–2230. https://doi.org/10.1016/j.ejrad.2016.10.020

Article  PubMed  Google Scholar 

Isaieva K, Leclère J, Felblinger J, Gillet R, Dubernard X, Vuissoz P-A (2023) Methodology for quantitative evaluation of mandibular condyles motion symmetricity from real-time MRI in the axial plane. Magn Reson Imaging 102:115–125. https://doi.org/10.1016/j.mri.2023.05.006

Article  PubMed  Google Scholar 

Mouchoux J, Meyer-Marcotty P, Sojka F, Dechent P, Klenke D, Wiechens B et al (2024) Reliability of landmark identification for analysis of the temporomandibular joint in real-time MRI. Head Face Med 20:10. https://doi.org/10.1186/s13005-024-00411-7

Article  PubMed  PubMed Central  Google Scholar 

Uecker M, Zhang S, Voit D, Karaus A, Merboldt K-D, Frahm J (2010) Real-time MRI at a resolution of 20 ms. NMR Biomed 23:986–994. https://doi.org/10.1002/nbm.1585

Article  PubMed  Google Scholar 

Ronneberger O, Fischer P, Brox T (2015) U-Net: convolutional networks for biomedical image segmentation. https://doi.org/10.48550/arXiv.1505.04597

Kirillov A, Mintun E, Ravi N, Mao H, Rolland C, Gustafson L et al. (2023) Segment anything. 2023 IEEE/CVF international conference on computer vision (ICCV), Paris, France: IEEE, pp 3992–4003. https://doi.org/10.1109/ICCV51070.2023.00371

Isaieva K, Leclère J, Paillart G, Drouot G, Felblinger J, Dubernard X et al (2024) Videos of axial and sagittal image series with segmented condyles and mutual slice position. Figshare. https://doi.org/10.6084/m9.figshare.25846300.v1

Wiesinger B, Häggman-Henrikson B, Wänman A, Lindkvist M, Hellström F (2014) Jaw-opening accuracy is not affected by masseter muscle vibration in healthy men. Exp Brain Res 232:3501–3508. https://doi.org/10.1007/s00221-014-4037-3

Article  CAS  PubMed  Google Scholar 

Prodoehl J, Thomas P, Krzak JJ, Hanke T, Tojanic J (2022) Effect of starting posture on three-dimensional jaw and head movement. J Oral Maxillofac Res 13:e1. https://doi.org/10.5037/jomr.2022.13104

Article  Google Scholar 

Talmaceanu D, Bolog N, Leucuta D, Tig IA, Buduru S (2022) Diagnostic use of computerized axiography in TMJ disc displacements. Exp Ther Med 23:1–8. https://doi.org/10.3892/etm.2022.11137

Article  Google Scholar 

Buduru S, Balhuc S, Ciumasu A, Kui A, Ciobanu C, Almasan O et al (2020) Temporomandibular dysfunction diagnosis by means of computerized axiography. Med Pharm Rep 93:416–421

PubMed  PubMed Central  Google Scholar