Academic literature on the topic 'Orthopantomogramme'
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Journal articles on the topic "Orthopantomogramme"
Douilly, G., M. A. Fauroux, and J. H. Torres. "Radio-opacités sur un orthopantomogramme." Revue de Stomatologie, de Chirurgie Maxillo-faciale et de Chirurgie Orale 114, no. 6 (December 2013): e17-e18. http://dx.doi.org/10.1016/j.revsto.2013.06.006.
Full textFaryal, Asma, and Attiya Shaikh. "RELIABILITY OF ORTHOPANTOMOGRAM IN COMPARISON TO LATERAL CEPHALOGRAM FOR LINEAR MANDIBULAR MEASUREMENTS." Journal of Ayub Medical College Abbottabad 34, no. 4(SUPPL 1) (October 11, 2022): 957–63. http://dx.doi.org/10.55519/jamc-04-s4-10338.
Full textFattah, Assit prof Dr Ahlam A. "Utilization of Orthopantomograms in Dental Radiology." Mustansiria Dental Journal 4, no. 1 (April 4, 2018): 30–32. http://dx.doi.org/10.32828/mdj.v4i1.579.
Full textPandey, Nashib, Sujaya Gupta, Ankit Shah, Anju Khapung, and Bhageshwar Dhami. "Sub Sinus Ridge Height at First Molar Region- A Panoramic Radiograph Based Study." Journal of Nepal Health Research Council 18, no. 2 (September 7, 2020): 243–47. http://dx.doi.org/10.33314/jnhrc.v18i2.2675.
Full textAyub, Iqra, Maryam Rehman, Maria Nawaz, Maria Jabbar, Hira Butt, and Fahmina Jamil. "Inter-Rater Reliability to the Assessment of Ramus Relationship of Mandibular Impacted Third Molar Among Denitsts: An Orthopantomographic Study." Pakistan Journal of Medical and Health Sciences 17, no. 1 (January 31, 2023): 394–96. http://dx.doi.org/10.53350/pjmhs2023171394.
Full textIsakova, O., and V. Makeev. "Assessment of the dynamics of x-ray morphometric indices of the jaws in children with variable bite." SUCHASNA STOMATOLOHIYA 106, no. 2 (2021): 68–74. http://dx.doi.org/10.33295/1992-576x-2021-2-68.
Full textShrestha, Vikash Veer, Ansu Piya, Anju Khapung, and Prakash Bhattarai. "Comparison of Accuracy of Gonial Angle of Orthopantomogram and Lateral Cephalogram for Mandibular Measurements among Orthodontic Patients Attending Tertiary Care Dental Hospital in Kathmandu." Orthodontic Journal of Nepal 10, no. 3 (December 31, 2020): 57–61. http://dx.doi.org/10.3126/ojn.v10i3.35497.
Full textKaur, Ravdeep, Rajan Kumar Singla, Ravikant Sharma, and Sanju Singla. "Localization of mandibular foramen – a comparison between dry bones and orthopantomogram." Journal of Medicine and Life 15, no. 5 (May 2022): 669–74. http://dx.doi.org/10.25122/jml-2022-0007.
Full textKadhom, Zainab M. "Radiological age estimation using third molars mineralization in a sample attending orthodontic clinics (A retrospective study)." Journal of Baghdad College of Dentistry 32, no. 1 (March 15, 2020): 57–64. http://dx.doi.org/10.26477/jbcd.v32i1.2759.
Full textKhanal, Sanskriti, Jemish Acharya, and Priyanka Shah. "Dental Age Estimation by Demirjian’s and Nolla’s Method in Children of Jorpati, Kathmandu." Journal of College of Medical Sciences-Nepal 14, no. 3 (September 30, 2018): 137–41. http://dx.doi.org/10.3126/jcmsn.v14i3.20733.
Full textDissertations / Theses on the topic "Orthopantomogramme"
Heiermann, Katrin [Verfasser]. "Vergleichende Untersuchung zur diagnostischen Wertigkeit von DVT-basierten Panoramarekonstruktionen und digitaler Orthopantomogramme für die chirurgische Anwendung / Katrin Heiermann." Köln : Deutsche Zentralbibliothek für Medizin, 2010. http://d-nb.info/1008978469/34.
Full textGalibourg, Antoine. "Estimation de l'âge dentaire chez le sujet vivant : application des méthodes d'apprentissage machine chez les enfants et les jeunes adultes." Electronic Thesis or Diss., Toulouse 3, 2022. http://thesesups.ups-tlse.fr/5355/.
Full textStatement of the problem: In the living individual, the estimation of dental age is a parameter used in orthopedics or dentofacial orthodontics or in pediatrics to locate the individual on its growth curve. In forensic medicine, the estimation of dental age allows to infer the chronological age for a regression or a classification task. There are physical and radiological methods. While the latter are more accurate, there is no universal method. Demirjian created the most widely used radiological method almost 50 years ago, but it is criticized for its accuracy and for using reference tables based on a French-Canadian population sample. Objective: Artificial intelligence, and more particularly machine learning, has allowed the development of various tools with a learning capacity on an annotated database. The objective of this thesis was to compare the performance of different machine learning algorithms first against two classical methods of dental age estimation, and then between them by adding additional predictors. Material and method: In a first part, the different methods of dental age estimation on living children and young adults are presented. The limitations of these methods are exposed and the possibilities to address them with the use of machine learning are proposed. Using a database of 3605 panoramic radiographs of individuals aged 2 to 24 years (1734 girls and 1871 boys), different machine learning methods were tested to estimate dental age. The accuracies of these methods were compared with each other and with two classical methods by Demirjian and Willems. This work resulted in an article published in the International Journal of Legal Medicine. In a second part, the different machine learning methods are described and discussed. Then, the results obtained in the article are put in perspective with the publications on the subject in 2021. Finally, a perspective of the results of the machine learning methods in relation to their use in dental age estimation is made. Results: The results show that all machine learning methods have better accuracy than the conventional methods tested for dental age estimation under the conditions of their use. They also show that the use of the maturation stage of third molars over an extended range of use to 24 years does not allow the estimation of dental age for a legal issue. Conclusion: Machine learning methods fit into the overall process of automating dental age determination. The specific part of deep learning seems interesting to investigate for dental age classification tasks
Hertel, Julia [Verfasser]. "Untersuchungen zur Eignung ausgewählter lebensalterassoziierter Merkmale hinsichtlich der forensischen Altersdiagnostik am Orthopantomogramm / Julia Hertel." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2012. http://d-nb.info/1026789249/34.
Full textBennemann, Ruth [Verfasser]. "Beurteilung der Position von Minischrauben per Orthopantomogramm im Vergleich zur digitalen Volumentomographie / Ruth Bennemann. Medizinische Fakultät." Bonn : Universitäts- und Landesbibliothek Bonn, 2011. http://d-nb.info/1017915687/34.
Full textAl-Borney, Majed. "Verwendung des Fernröntgenseitenbildes des Kopfes und des Orthopantomogramms zur metrischen Analyse des Schädels in der Kieferorthopädie eine vergleichende Studie /." [S.l.] : [s.n.], 1999. http://deposit.ddb.de/cgi-bin/dokserv?idn=958489130.
Full textBös, Carolin [Verfasser]. "Projektion kalzifizierender Plaque der Karotiden in der zahnärztlich-röntgenologischen Panoramaschichtaufnahme (Orthopantomogramm) / Carolin Bös geb. Mues." 2009. http://d-nb.info/1000724328/34.
Full textRiekert, Maximilian. "Wertigkeit klinischer, instrumenteller und bildgebender Untersuchungsverfahren der Kiefergelenksdiagnostik bei Patienten mit juveniler idiopathischer Arthritis." Doctoral thesis, 2018. https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-163762.
Full textSummary Aim: Pathomorphological changes of the temporomandibular joints occur frequently in patients with JIA. In this study, orthodontic two-dimensional X-ray imaging (orthopantomography - OPG) was used to differentiate pathological changes of the temporomandibular joints in JIA patients and to determine asymmetries of the mandible in accordance to the degree of condyle destruction. In addition, it should be examined how the disease duration affects the involvement of the temporomandibular joints. In addition, clinical analysis (FAL), joint vibration analysis (JVA) and 3D stereophotogrammetry (3d-scan) were used for the specific analysis of pathomorphology. The aim was to detect unambiguous parameters for affected temporomandibular joints by means of non-invasive, cost-effective and rapidly available examination methods. Patients and methods: In this study, 46 patients (28 female, 18 male) of Caucasian origin were diagnosed with JIA. The temporomandibular joints (n = 92) were individually evaluated based on the degree of their condylar destruction (Grades 0 - 4 according to Billiau et al. [78]) and divided into a slightly affected group 1 (Grades 0, 1 and 2 according to Billiau: radiologically unremarkable, Condylar erosions, condyle flattening) and into a severely affected group 2 (grade 3 and 4 according to Billiau: condyle flattening with erosions, complete loss of the condyle). To quantify mandibular asymmetries, the ratio of condyle, ramus and mandibular height was determined. The comparison of the individual clinical, instrumental and imaging examination procedures (OPG, FAL, JVA, 3d-Scan) was performed by comparing the severely affected and the slightly affected patient group. Results: Disease duration: Based on the degree of condylar destruction, 36 patients were divided into the slightly affected group 1 and 10 patients to the severely affected group 2. The disease duration was significantly longer in the severely affected patient group (8.9 ± 5.2 years) than in the slightly affected patient group (4.6 ± 4.7 years) (p = 0.031). FAL: The results of the FAL showed more functional deviations in the severely affected patient group (group 2). However, no significant difference to Group 1 was found. The severely affected patients showed a higher percentage of pain in palpation of the temporomandibular joints (group 2: 70.0% vs. group 1: 61.1%) or mouth opening pain (group 2: 10.0% vs. group 1: 8.3%), mandibular deflections (group 2: 50.0% vs. group 1: 33.3%), joint noises (group 2: 80.0% vs. group 1: 63.9%) and mouth opening restrictions (Group 2: 60.0% vs. Group 1: 25.0%). The average mouth opening in group 2 was 40.6 mm, while in group 1 it was 43.5 mm. In patients with a mouth opening <40 mm, an average mouth opening of 35.3 mm was measured in group 2 and 34.1 mm in group 1. JVA: In the joint-related as well as in the patient-group-related analysis of the JVA, the measurement parameters in the severely affected patient group increasingly pointed to chronic degenerative or existing effusions in the temporomandibular joint. In the joint-related evaluation, this was demonstrated in particular by a reduced signal strength in the severely affected patient group (total power: p = 0.005, power <300 Hz: p = 0.006, power> 300 Hz: 0.003;) and in a significantly increased peak frequency (p = 0.036). OPG: In the evaluation of the OPGs, the ratio of condyle, ramus and mandibular height was significantly lower in the severe patient group (ratio 79.6%, 85.9%, 86.5%) (condyle height: p = 0.0005; p = 0.0030, mandibular height: p = 0.0002), than in the slightly affected Patient group (ratio 93.8%, ratio 96.0%, 95.6%). Thus, significantly more pronounced mandibular asymmetries were found in the severely affected patient group than in the slightly affected patient group. 3d scan: In the 3d scan, deviations of the soft tissue chin from the median plane (group 2: 3.0 mm vs. group 1: 1.2 mm, p = 0.041) and mandibular asymmetry were significantly more frequent in patients with severely affected temporomandibular joints (group 2: 62.5% vs. Group 1: 14.8%, p = 0.015) than in patients with slightly affected temporomandibular joints. Conclusion: It has been shown that it is possible to visualize pathology in the temporomandibular joint by means of simple and easily available examination methods such as clinical functional analysis, joint vibration analysis and OPG imaging. The methods can serve as an important reference for controlling disease progression in patients with JIA. In addition, a classification of the condyles in severe and slightly affected temporomandibular joints by means of pathomorphological analysis is possible. There is a direct correlation between the degree of destruction, the extent of mandibular asymmetry and the duration of the disease in patients with JIA. Overall, the value of clinical, instrumental and imaging examination methods of temporomandibular joint diagnosis in patients with juvenile idiopathic arthritis was demonstrated
Bugger, Marius [Verfasser]. "Detektion endodontisch erkrankter Zähne : Stellenwert des Orthopantomogramms als Additivum zur klinischen Befunderhebung / vorgelegt von Marius Bugger." 2008. http://d-nb.info/989479919/34.
Full textPfaffmann, Georg [Verfasser]. "Möglichkeiten, Aussagekraft und Grenzen der zahnärztlichen Diagnostik mit dem Orthopantomogramm (OPG) - Befunde einer empirischen Langfrist-Untersuchung / vorgelegt von Pfaffmann, Georg." 2008. http://d-nb.info/987914294/34.
Full textAl-Borney, Majed [Verfasser]. "Verwendung des Fernröntgenseitenbildes des Kopfes und des Orthopantomogramms zur metrischen Analyse des Schädels in der Kieferorthopädie : eine vergleichende Studie / vorgelegt von Majed Al-Borney." 1999. http://d-nb.info/958489130/34.
Full textBook chapters on the topic "Orthopantomogramme"
Mathur, Romir, Gopal Sakarkar, Kamlesh Kalbande, Rishi Mathur, Hrugved Kolhe, and Harish Rathi. "Orthopantomogram (OPG) Image Analysis Using Bounding Box Algorithm." In Computational Methods and Data Engineering, 55–65. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3015-7_5.
Full textHsu, Tzu-Ming Harry, and Yin-Chih Chelsea Wang. "DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 366–76. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87240-3_35.
Full textFrejlichowski, Dariusz, and Robert Wanat. "Automatic Segmentation of Digital Orthopantomograms for Forensic Human Identification." In Image Analysis and Processing – ICIAP 2011, 294–302. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24088-1_31.
Full textFrejlichowski, Dariusz, and Robert Wanat. "Extraction of Teeth Shapes from Orthopantomograms for Forensic Human Identification." In Computer Analysis of Images and Patterns, 65–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23678-5_6.
Full textFrejlichowski, Dariusz, and Piotr Czapiewski. "An Application of the Curvature Scale Space Shape Descriptor for Forensic Human Identification Based on Orthopantomograms." In Computer Information Systems and Industrial Management, 67–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40925-7_7.
Full textNötzel, Frank, and Christian Schultz. "5 Orthopantomogramm." In Leitfaden der kieferorthopädischen Diagnostik, 97–118. Deutscher Zahnärzte Verlag, 2008. http://dx.doi.org/10.47420/9783769137194-97.
Full text"Orthopantomogramm des Kiefer- und Gesichtsschädels." In Röntgennormalbefunde, edited by Torsten B. Möller. Stuttgart: Georg Thieme Verlag, 2015. http://dx.doi.org/10.1055/b-0035-103208.
Full text"Orthopantomogramm des Kiefer- und Gesichtsschädels." In Röntgennormalbefunde, edited by Torsten Möller. Stuttgart: Georg Thieme Verlag, 2003. http://dx.doi.org/10.1055/b-0034-17469.
Full textSadaksharam, Jayachandran, and Ashita Kalaskar. "Dental Radiology in Pediatric Dentistry." In Illustrated Pediatric Dentistry - Part 2, 57–83. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815080773123010008.
Full textConference papers on the topic "Orthopantomogramme"
Mouraret, A., E. Gerard, J. Le Gall, and R. Curien. "Ostéonécrose du prémaxillaire consécutive à une coagulation intravasculaire disséminée : à propos d’un cas." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206603011.
Full textMikulka, Jan, Miroslav Kabrda, Eva Gescheidtova, and Vojtech Perina. "Classification of jawbone cysts via orthopantomogram processing." In 2012 35th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2012. http://dx.doi.org/10.1109/tsp.2012.6256344.
Full textHeinrich, A., M. Engler, L. Richter, D. Ramma, F. Güttler, and U. Teichgräber. "Deep Learning zur automatisierten Zahnklassifizierung und -segmentierung von Orthopantomogrammen." In 103. Deutscher Röntgenkongress der Deutschen Röntgengesellschaft e. V. Georg Thieme Verlag, 2022. http://dx.doi.org/10.1055/s-0042-1749761.
Full textAlande, C., and C. Landric. "Autotransplantation de germes dentaires au centre hospitalier de Pau : une série de cas." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206603008.
Full textZhang, Hua, S. H. Ong, K. W. C. Foong, and T. Dhar. "3-dimensional orthodontics visualization system with dental study models and orthopantomograms." In SPIE Proceedings, edited by Jose F. Lopez, Chenggen Quan, Fook Siong Chau, Francisco V. Fernandez, Jose Maria Lopez-Villegas, Anand Asundi, Brian Stephen Wong, Jose M. de la Rosa, and Chwee Teck Lim. SPIE, 2005. http://dx.doi.org/10.1117/12.621914.
Full textAseretto, Sebastian Gonzalez, and Jose Luis Vazquez Noguera. "Contrast enhancement of orthopantomograms to improve tooth segmentation using U-Nets." In 2022 XVLIII Latin American Computer Conference (CLEI). IEEE, 2022. http://dx.doi.org/10.1109/clei56649.2022.9959912.
Full textLaishram, Anuradha, and Khelchandra Thongam. "Detection and Classification of Dental Pathologies using Faster-RCNN in Orthopantomogram Radiography Image." In 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2020. http://dx.doi.org/10.1109/spin48934.2020.9071242.
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