Image Processing Techniques Applied to Oral Medicine
Abstract
This thesis’ main objective is to investigate the applicability of image processing techniques in the oral imaging field, through a selection of oral issues use cases that can be mapped into different computational tasks. In order to investigate the validity of this approach, a series of methods are proposed employing different IP techniques. This work presents a compilation of these different solutions as an unique toolset to be employed in clinical scenarios, assisting oral medicine experts in several tasks with decision-supporting algorithms for diagnosis of oral issues, instead of only providing visualization interfaces for image exams as current commercial solutions.References
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Dong, C., Loy, C. C., He, K., and Tang, X. (2015). Image super-resolution using deep convolutional networks. IEEE transactions on pattern analysis and machine intelligence, 38(2):295–307.
Ledig, C., Theis, L., Huszár, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani, A., Totz, J., Wang, Z., et al. (2017). Photo-realistic single image super-resolution using a generative adversarial network. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4681–4690.
Moran, M. B., Faria, M. D., Giraldi, G. A., Bastos, L. F., and Conci, A. (2020). Using super-resolution generative adversarial network models and transfer learning to obtain high resolution digital periapical radiographs. Computers in biology and medicine, 129:104139.
Schwendicke, F., Golla, T., Dreher, M., and Krois, J. (2019). Convolutional neural networks for dental image diagnostics: A scoping review. Journal of Dentistry, 91:103226.
Schwendicke, F., Samek, W., and Krois, J. (2020). Artificial intelligence in dentistry: Chances and challenges. Journal of Dental Research, page 0022034520915714.
Published
2025-06-09
How to Cite
MORAN, Maira B. H.; CONCI, Aura.
Image Processing Techniques Applied to Oral Medicine. In: ARTUR ZIVIANI AWARD - THESES AND DISSERTATIONS CONTEST (PHD) - BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTHCARE (SBCAS), 25. , 2025, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 181-186.
ISSN 2763-8987.
DOI: https://doi.org/10.5753/sbcas_estendido.2025.7042.
