Computational Filters for Dental and Oral Lesion Visualization in Spectral Images

Clinically interesting low-contrast dental and oral features can be challenging to detect. In visual observation and clinical photographs, identification of low-contrast features can be hard or even impossible. Imaging methods, e.g., X-ray and magnetic resonance imaging, provide more information but...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Joni Hyttinen, Pauli Falt, Heli Jasberg, Arja Kullaa, Markku Hauta-Kasari
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Contrast enhancement dentistry oral mucosa principal component analysis spectral imaging teeth Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/f63f30ec79c14fa99fae4ee01e01f15f
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:f63f30ec79c14fa99fae4ee01e01f15f
record_format	dspace
spelling	oai:doaj.org-article:f63f30ec79c14fa99fae4ee01e01f15f2021-11-10T00:01:14ZComputational Filters for Dental and Oral Lesion Visualization in Spectral Images2169-353610.1109/ACCESS.2021.3121815https://doaj.org/article/f63f30ec79c14fa99fae4ee01e01f15f2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9583296/https://doaj.org/toc/2169-3536Clinically interesting low-contrast dental and oral features can be challenging to detect. In visual observation and clinical photographs, identification of low-contrast features can be hard or even impossible. Imaging methods, e.g., X-ray and magnetic resonance imaging, provide more information but often require use of ionizing radiation, expensive equipment, and specialized personnel to operate the devices. A cost-effective, non-ionizing, contrast-enhancing imaging method that can be used at any dental clinic is in great demand. Here we show a dental and oral feature visibility-enhancement based on a portable spectral camera and computational filters derived from principal component analysis. By applying computational filters on oral and dental spectral images, selected features of clinical interest can be highlighted against their surroundings. Due to the lack of information available in standard color images, this visibility-enhancement technique can only be realized using spectral images. Oral and dental spectral imaging does not use ionizing radiation, and modern spectral cameras are small, portable, and can be used without specialized training. In this paper, spectral image-based visibility-enhancement is demonstrated for the following cases: gingival recession, calculus, gingivitis, root caries, secondary caries, Fordyce’s granules, leukoplakia, and pigmentous lesions. The results gained with spectral images and computational filters from principal component analysis are compared against regular color images and grayscale images computed with band-pass filters from our earlier work. The results are promising as the visibility and contrast of the features of interests are enhanced in all the studied cases. This study provides a starting point for future research and demonstrates the applicability of spectral imaging-based methods for practical use at dental clinics.Joni HyttinenPauli FaltHeli JasbergArja KullaaMarkku Hauta-KasariIEEEarticleContrast enhancementdentistryoral mucosaprincipal component analysis spectral imagingteethElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 145148-145160 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Contrast enhancement dentistry oral mucosa principal component analysis spectral imaging teeth Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Contrast enhancement dentistry oral mucosa principal component analysis spectral imaging teeth Electrical engineering. Electronics. Nuclear engineering TK1-9971 Joni Hyttinen Pauli Falt Heli Jasberg Arja Kullaa Markku Hauta-Kasari Computational Filters for Dental and Oral Lesion Visualization in Spectral Images
description	Clinically interesting low-contrast dental and oral features can be challenging to detect. In visual observation and clinical photographs, identification of low-contrast features can be hard or even impossible. Imaging methods, e.g., X-ray and magnetic resonance imaging, provide more information but often require use of ionizing radiation, expensive equipment, and specialized personnel to operate the devices. A cost-effective, non-ionizing, contrast-enhancing imaging method that can be used at any dental clinic is in great demand. Here we show a dental and oral feature visibility-enhancement based on a portable spectral camera and computational filters derived from principal component analysis. By applying computational filters on oral and dental spectral images, selected features of clinical interest can be highlighted against their surroundings. Due to the lack of information available in standard color images, this visibility-enhancement technique can only be realized using spectral images. Oral and dental spectral imaging does not use ionizing radiation, and modern spectral cameras are small, portable, and can be used without specialized training. In this paper, spectral image-based visibility-enhancement is demonstrated for the following cases: gingival recession, calculus, gingivitis, root caries, secondary caries, Fordyce’s granules, leukoplakia, and pigmentous lesions. The results gained with spectral images and computational filters from principal component analysis are compared against regular color images and grayscale images computed with band-pass filters from our earlier work. The results are promising as the visibility and contrast of the features of interests are enhanced in all the studied cases. This study provides a starting point for future research and demonstrates the applicability of spectral imaging-based methods for practical use at dental clinics.
format	article
author	Joni Hyttinen Pauli Falt Heli Jasberg Arja Kullaa Markku Hauta-Kasari
author_facet	Joni Hyttinen Pauli Falt Heli Jasberg Arja Kullaa Markku Hauta-Kasari
author_sort	Joni Hyttinen
title	Computational Filters for Dental and Oral Lesion Visualization in Spectral Images
title_short	Computational Filters for Dental and Oral Lesion Visualization in Spectral Images
title_full	Computational Filters for Dental and Oral Lesion Visualization in Spectral Images
title_fullStr	Computational Filters for Dental and Oral Lesion Visualization in Spectral Images
title_full_unstemmed	Computational Filters for Dental and Oral Lesion Visualization in Spectral Images
title_sort	computational filters for dental and oral lesion visualization in spectral images
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/f63f30ec79c14fa99fae4ee01e01f15f
work_keys_str_mv	AT jonihyttinen computationalfiltersfordentalandorallesionvisualizationinspectralimages AT paulifalt computationalfiltersfordentalandorallesionvisualizationinspectralimages AT helijasberg computationalfiltersfordentalandorallesionvisualizationinspectralimages AT arjakullaa computationalfiltersfordentalandorallesionvisualizationinspectralimages AT markkuhautakasari computationalfiltersfordentalandorallesionvisualizationinspectralimages
_version_	1718440801731608576

Computational Filters for Dental and Oral Lesion Visualization in Spectral Images

Ejemplares similares