Detection and classification of mandibular fracture on CT scan using deep convolutional neural network
Author:
Funder
National Key Research and Development Program of China
Publisher
Springer Science and Business Media LLC
Subject
General Dentistry
Link
https://link.springer.com/content/pdf/10.1007/s00784-022-04427-8.pdf
Reference40 articles.
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2. Boffano P, Kommers SC, Roccia F, Forouzanfar T (2015) Mandibular trauma treatment: a comparison of two protocols. Medicina oral, patologia oral y cirugia bucal 20:e218–e223. https://doi.org/10.4317/medoral.20263
3. Boffano P, Roccia F, Zavattero E, Dediol E, Uglešić V, Kovačič Ž, Vesnaver A, Konstantinović VS, Petrović M, Stephens J, Kanzaria A, Bhatti N, Holmes S, Pechalova PF, Bakardjiev AG, Malanchuk VA, Kopchak AV, Galteland P, Mjøen E, Skjelbred P, Koudougou C, Mouallem G, Corre P, Løes S, Lekven N, Laverick S, Gordon P, Tamme T, Akermann S, Karagozoglu KH, Kommers SC, Forouzanfar T (2015) European Maxillofacial Trauma (EURMAT) project: a multicentre and prospective study. Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery 43:62–70. https://doi.org/10.1016/j.jcms.2014.10.011
4. He D, Zhang Y, Ellis E 3rd (2007) Panfacial fractures: analysis of 33 cases treated late. Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons 65:2459–2465. https://doi.org/10.1016/j.joms.2007.06.625
5. Shen D, Wu G, Suk HI (2017) Deep Learning in Medical Image Analysis. Annu Rev Biomed Eng 19:221–248. https://doi.org/10.1146/annurev-bioeng-071516-044442
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