Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique

Sahand Shahalinejad

doi:doi:10.11648/j.ijdm.20210702.11

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Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique

Sahand Shahalinejad

Published in International Journal of Dental Medicine (Volume 7, Issue 2)

Received: 11 May 2021 Accepted: 8 July 2021 Published: 16 July 2021

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Abstract

Oral disease is one of the most common causes of death in some countries. Changing habits and diet, not observing oral hygiene, neglecting the importance and health of teeth are the most important causes of oral diseases, these diseases may be specific to the oral cavity or may contribute to the disease in humans as part of an incompatible substance. In the meantime, the field of image processing has been proposed to provide automatic systems for disease diagnosis. Among medical image processing methods, image edging is the process of identifying and changing the display of an image. The purpose of this study is to use the edge recognition method and compare it with previous algorithms to be able to more accurately identify oral tissue from biological materials used in teeth than in the past. In the present study, using the method of Image segmentation (edge detection) is labeled for each pixel, so that pixels with the same label have similar properties. Oral and dental tissue segmentation was performed. Quantitative analysis of the results showed an accuracy of over 80% of the proposed method for oral tissue diagnosis. So that by using the results, it is possible to best identify a person who has a lesion in the tooth or oral tissue.

Published in	International Journal of Dental Medicine (Volume 7, Issue 2)
DOI	10.11648/j.ijdm.20210702.11
Page(s)	15-19
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Oral Tissue, Dental Images, Edge Detection, Segmentation, Image Processing

References

[1]	American Academy of Oral Medicine (AAOM). Subject: oral cancer screening [accessed 2019 June 4]. https://www.aaom.com/clinical-practice-statement-oral-cancer-screening
[2]	Farah, CS, Dost, F, Do, L. Usefulness of optical fluorescence imaging in identification and triaging of oral potentially malignant disorders: a study of VELscope in the LESIONS programme. J Oral Pathol Med. 2019. 48 (7): 581–587. Google Scholar \| Crossref \| Medline.
[3]	Firmalino, V, Anbarani, A, Islip, D, Song, B, Uthoff, R, Takesh, T, Liang, R, Wilder-Smith, P. 2018. First clinical results: optical smartphone-based oral cancer screening. Paper presented at 38th American Society for Laser Surgery and Medicine Annual Meeting; April 11–15, 2018; Dallas, TX.
[4]	Grafton-Clarke, C, Chen, KW, Wilcock, J. Diagnosis and referral delays in primary care for oral squamous cell cancer: a systematic review. Br J Gen Pract. 2019. 69, (679): e112–e126.
[5]	Kuriakose, MA. Strategies to improve oral cancer outcome in high-prevalent, low-resource setting. J Head Neck Physicians Surg. 2018. 6 (2): 63–68I.
[6]	T. A. A. Tosta, P. R. de Faria, J. P. S. Servato, L. A. Neves, G. F. Roberto, A. S. Martins, et al., "Unsupervised method for normalization of hematoxylin-eosin stain in histological images", Comput. Med. Imaging Graph. vol. 77, 2019.
[7]	A. Vahadane, T. Peng, A. Sethi, S. Albarqouni, L. Wang, M. Baust, et al., "Structure-preserving color normalization and sparse stain separation for histological images", IEEE Trans. Med. Image., vol. 35, no. 8, pp. 1962-1971, 2016.
[8]	O’Connor, JP, Rose, CJ, Waterton, JC, Carano, RA, Parker, GJ, Jackson, A. Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome. Clin Cancer Res. 2015. 21 (2): 249–257.
[9]	Simonato, LE, Tomo, S, Miyahara, GI, Navarro, RS, Villaverde, AGJB. Fluorescence visualization efficacy for detecting oral lesions more prone to be dysplastic and potentially malignant disorders: a pilot study. Photo diagnosis Photodyn Ther. 2017. 64, 17: 1–4.
[10]	Simonato, LE, Tomo, S, Navarro, RS, Villaverde, AGJB. Fluorescence visualization improves the detection of oral, potentially malignant, disorders in population screening. Photo diagnosis Photodyn Ther. 2019. 27: 74–78.
[11]	Song, S, Sunny, S, Uthoff, RD, Patrick, S, Suresh, A, Kolur, T, Keerthi, G, Anbarani, A, Wilder-Smith, P, Kuriakose, MA, et al. Automatic classification of dual-modality, smartphone-based oral dysplasia and malignancy images using deep learning. Biomed Opt Express. 2018. 9 (11): 5318–5329.
[12]	Sunny, SP, Agarwal, S, James, BL, Heidari, E, Muralidharan, A, Yadav, V, Pillai, V, Shetty, V, Chen, Z, Hedne, N, et al. Intra-operative point-of-procedure delineation of oral cancer margins using optical coherence tomography. Oral Oncol. 2019. 92: 12–19.
[13]	Tiwari, L, Kujan, O, Farah, CS. Optical fluorescence imaging in oral cancer and potentially malignant disorders: a systematic review. Oral Dis [pub ahead of print 27 Feb 2019].
[14]	Uthoff, RD, Song, B, Birur, P, Kuriakose, MA, Sunny, S, Suresh, A, Patrick, S, Anbarani, A, Spires, O, Wilder-Smith, P, et al. Development of a dual-modality, dual-view smartphone-based imaging system for oral cancer detection. Proceedings of SPIE 10486, Design and Quality for Biomedical Technologies XI. 2018.10486.
[15]	Webster, JD, Batstone, M, Farah, CS. Missed opportunities for oral cancer screening in Australia. J Oral Pathol Med. 2019.48 (7): 595–603.
[16]	Yang, EC, Tan, MT, Schwarz, RA, Richards-Kortum, RR, Gillenwater, AM, Vigneswaran, N. Noninvasive diagnostic adjuncts for the evaluation of potentially premalignant oral epithelial lesions: current limitations and future directions. Oral Surg Oral Med Oral Pathol Oral Radiol. 2018. 125 (6): 670–681.
[17]	Zhou, H, Chen, M, Rehg, JM. Dermoscopic interest point detector and descriptor. Paper presented at Proceedings of the 6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBIâTM09); 2009 Oct 11; Boston, MA.
[18]	A. Vahadane and A. Sethi, "Towards generalized nuclear segmentation in histological images", 13th IEEE International Conference on Bioinformatics and Bioengineering. 2013. pp. 1-4.
[19]	D. P. Kingma and J. Ba, Adam: A method for stochastic optimization, 2014.
[20]	A. A. Tirodkar, “A Multi-Stage Algorithm for Enhanced X-Ray Image Segmentation”, International Journal of Engineering Science and Technology (IJEST), Vol. 3 No. 9, pp. 7056-7065.
[21]	S. K. Mahendran and S. S. Baboo, “Enhanced automatic X-ray bone image segmentation using wavelets and morphological operators”, Proc. of the International Conference on Information and Electronics Engineering, 2011.

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APA Style

Sahand Shahalinejad. (2021). Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique. International Journal of Dental Medicine, 7(2), 15-19. https://doi.org/10.11648/j.ijdm.20210702.11

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ACS Style

Sahand Shahalinejad. Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique. Int. J. Dent. Med. 2021, 7(2), 15-19. doi: 10.11648/j.ijdm.20210702.11

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AMA Style

Sahand Shahalinejad. Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique. Int J Dent Med. 2021;7(2):15-19. doi: 10.11648/j.ijdm.20210702.11

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@article{10.11648/j.ijdm.20210702.11,
  author = {Sahand Shahalinejad},
  title = {Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique},
  journal = {International Journal of Dental Medicine},
  volume = {7},
  number = {2},
  pages = {15-19},
  doi = {10.11648/j.ijdm.20210702.11},
  url = {https://doi.org/10.11648/j.ijdm.20210702.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdm.20210702.11},
  abstract = {Oral disease is one of the most common causes of death in some countries. Changing habits and diet, not observing oral hygiene, neglecting the importance and health of teeth are the most important causes of oral diseases, these diseases may be specific to the oral cavity or may contribute to the disease in humans as part of an incompatible substance. In the meantime, the field of image processing has been proposed to provide automatic systems for disease diagnosis. Among medical image processing methods, image edging is the process of identifying and changing the display of an image. The purpose of this study is to use the edge recognition method and compare it with previous algorithms to be able to more accurately identify oral tissue from biological materials used in teeth than in the past. In the present study, using the method of Image segmentation (edge detection) is labeled for each pixel, so that pixels with the same label have similar properties. Oral and dental tissue segmentation was performed. Quantitative analysis of the results showed an accuracy of over 80% of the proposed method for oral tissue diagnosis. So that by using the results, it is possible to best identify a person who has a lesion in the tooth or oral tissue.},
 year = {2021}
}

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TY  - JOUR
T1  - Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique
AU  - Sahand Shahalinejad
Y1  - 2021/07/16
PY  - 2021
N1  - https://doi.org/10.11648/j.ijdm.20210702.11
DO  - 10.11648/j.ijdm.20210702.11
T2  - International Journal of Dental Medicine
JF  - International Journal of Dental Medicine
JO  - International Journal of Dental Medicine
SP  - 15
EP  - 19
PB  - Science Publishing Group
SN  - 2472-1387
UR  - https://doi.org/10.11648/j.ijdm.20210702.11
AB  - Oral disease is one of the most common causes of death in some countries. Changing habits and diet, not observing oral hygiene, neglecting the importance and health of teeth are the most important causes of oral diseases, these diseases may be specific to the oral cavity or may contribute to the disease in humans as part of an incompatible substance. In the meantime, the field of image processing has been proposed to provide automatic systems for disease diagnosis. Among medical image processing methods, image edging is the process of identifying and changing the display of an image. The purpose of this study is to use the edge recognition method and compare it with previous algorithms to be able to more accurately identify oral tissue from biological materials used in teeth than in the past. In the present study, using the method of Image segmentation (edge detection) is labeled for each pixel, so that pixels with the same label have similar properties. Oral and dental tissue segmentation was performed. Quantitative analysis of the results showed an accuracy of over 80% of the proposed method for oral tissue diagnosis. So that by using the results, it is possible to best identify a person who has a lesion in the tooth or oral tissue.
VL  - 7
IS  - 2
ER  -

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Author Information

Sahand Shahalinejad

Department of Bio Medical Engineering, Urmia Graduate Institute, Urmia, Iran

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Plain Text BibTeX RIS

APA Style

Sahand Shahalinejad. (2021). Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique. International Journal of Dental Medicine, 7(2), 15-19. https://doi.org/10.11648/j.ijdm.20210702.11

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ACS Style

Sahand Shahalinejad. Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique. Int. J. Dent. Med. 2021, 7(2), 15-19. doi: 10.11648/j.ijdm.20210702.11

Copy | Download

AMA Style

Sahand Shahalinejad. Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique. Int J Dent Med. 2021;7(2):15-19. doi: 10.11648/j.ijdm.20210702.11

Copy | Download

@article{10.11648/j.ijdm.20210702.11,
  author = {Sahand Shahalinejad},
  title = {Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique},
  journal = {International Journal of Dental Medicine},
  volume = {7},
  number = {2},
  pages = {15-19},
  doi = {10.11648/j.ijdm.20210702.11},
  url = {https://doi.org/10.11648/j.ijdm.20210702.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdm.20210702.11},
  abstract = {Oral disease is one of the most common causes of death in some countries. Changing habits and diet, not observing oral hygiene, neglecting the importance and health of teeth are the most important causes of oral diseases, these diseases may be specific to the oral cavity or may contribute to the disease in humans as part of an incompatible substance. In the meantime, the field of image processing has been proposed to provide automatic systems for disease diagnosis. Among medical image processing methods, image edging is the process of identifying and changing the display of an image. The purpose of this study is to use the edge recognition method and compare it with previous algorithms to be able to more accurately identify oral tissue from biological materials used in teeth than in the past. In the present study, using the method of Image segmentation (edge detection) is labeled for each pixel, so that pixels with the same label have similar properties. Oral and dental tissue segmentation was performed. Quantitative analysis of the results showed an accuracy of over 80% of the proposed method for oral tissue diagnosis. So that by using the results, it is possible to best identify a person who has a lesion in the tooth or oral tissue.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Detection of Oral and Dental Tissue from the Biomaterials Used in Teeth Using Medical Image Processing Technique
AU  - Sahand Shahalinejad
Y1  - 2021/07/16
PY  - 2021
N1  - https://doi.org/10.11648/j.ijdm.20210702.11
DO  - 10.11648/j.ijdm.20210702.11
T2  - International Journal of Dental Medicine
JF  - International Journal of Dental Medicine
JO  - International Journal of Dental Medicine
SP  - 15
EP  - 19
PB  - Science Publishing Group
SN  - 2472-1387
UR  - https://doi.org/10.11648/j.ijdm.20210702.11
AB  - Oral disease is one of the most common causes of death in some countries. Changing habits and diet, not observing oral hygiene, neglecting the importance and health of teeth are the most important causes of oral diseases, these diseases may be specific to the oral cavity or may contribute to the disease in humans as part of an incompatible substance. In the meantime, the field of image processing has been proposed to provide automatic systems for disease diagnosis. Among medical image processing methods, image edging is the process of identifying and changing the display of an image. The purpose of this study is to use the edge recognition method and compare it with previous algorithms to be able to more accurately identify oral tissue from biological materials used in teeth than in the past. In the present study, using the method of Image segmentation (edge detection) is labeled for each pixel, so that pixels with the same label have similar properties. Oral and dental tissue segmentation was performed. Quantitative analysis of the results showed an accuracy of over 80% of the proposed method for oral tissue diagnosis. So that by using the results, it is possible to best identify a person who has a lesion in the tooth or oral tissue.
VL  - 7
IS  - 2
ER  -

Copy | Download