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Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology

Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 111421, Paraguay
Facultad de Odontología, Universidad Nacional de Asunción, Asunción 001218, Paraguay
Departamento de Odontologia Restauradora, Faculdade de Odontologia de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14040-904, SP, Brazil
Facultad de Ciencias Exactas y Tecnológicas, Universidad Nacional de Conepción, Concepción 010123, Paraguay
Department of Computer and Electronics, Universidade Federal do Espírito Santo, São Mateus 29932-540, ES, Brazil
Author to whom correspondence should be addressed.
Academic Editor: Alireza Sadr
Sensors 2021, 21(9), 3110;
Received: 18 February 2021 / Revised: 26 April 2021 / Accepted: 27 April 2021 / Published: 29 April 2021
(This article belongs to the Special Issue Sensing and Imaging Technology in Dentistry)
Panoramic dental radiography is one of the most used images of the different dental specialties. This radiography provides information about the anatomical structures of the teeth. The correct evaluation of these radiographs is associated with a good quality of the image obtained. In this study, 598 patients were consecutively selected to undergo dental panoramic radiography at the Department of Radiology of the Faculty of Dentistry, Universidad Nacional de Asunción. Contrast enhancement techniques are used to enhance the visual quality of panoramic dental radiographs. Specifically, this article presents a new algorithm for contrast, detail and edge enhancement of panoramic dental radiographs. The proposed algorithm is called Multi-Scale Top-Hat transform powered by Geodesic Reconstruction for panoramic dental radiography enhancement (MSTHGR). This algorithm is based on multi-scale mathematical morphology techniques. The proposal extracts multiple features of brightness and darkness, through the reconstruction of the marker (obtained by the Top-Hat transformation by reconstruction) starting from the mask (obtained by the classic Top-Hat transformation). The maximum characteristics of brightness and darkness are added to the dental panoramic radiography. In this way, the contrast, details and edges of the panoramic radiographs of teeth are improved. For the tests, MSTHGR was compared with the following algorithms: Geodesic Reconstruction Multiscale Morphology Contrast Enhancement (GRMMCE), Histogram Equalization (HE), Brightness Preserving Bi-Histogram Equalization (BBHE), Dual Sub-Image Histogram Equalization (DSIHE), Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE), Quadri-Histogram Equalization with Limited Contrast (QHELC), Contrast-Limited Adaptive Histogram Equalization (CLAHE) and Gamma Correction (GC). Experimentally, the numerical results show that the MSTHGR obtained the best results with respect to the Contrast Improvement Ratio (CIR), Entropy (E) and Spatial Frequency (SF) metrics. This indicates that the algorithm performs better local enhancements on panoramic radiographs, improving their details and edges. View Full-Text
Keywords: panoramic dental radiography; contrast enhancement; multi-scale mathematical morphology; top-hat transformation panoramic dental radiography; contrast enhancement; multi-scale mathematical morphology; top-hat transformation
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MDPI and ACS Style

Román, J.C.M.; Fretes, V.R.; Adorno, C.G.; Silva, R.G.; Noguera, J.L.V.; Legal-Ayala, H.; Mello-Román, J.D.; Torres, R.D.E.; Facon, J. Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology. Sensors 2021, 21, 3110.

AMA Style

Román JCM, Fretes VR, Adorno CG, Silva RG, Noguera JLV, Legal-Ayala H, Mello-Román JD, Torres RDE, Facon J. Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology. Sensors. 2021; 21(9):3110.

Chicago/Turabian Style

Román, Julio C.M., Vicente R. Fretes, Carlos G. Adorno, Ricardo G. Silva, José L.V. Noguera, Horacio Legal-Ayala, Jorge D. Mello-Román, Ricardo D.E. Torres, and Jacques Facon. 2021. "Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology" Sensors 21, no. 9: 3110.

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