Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection

A. Z. Arifin; M. Hadi; A. Yuniarti; W. Khotimah; A. Yudhi; E. R. Astuti

doi:10.1109/SCIS-ISIS.2012.6505362

Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection

A. Z. Arifin, M. Hadi, A. Yuniarti, W. Khotimah, A. Yudhi, E. R. Astuti

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Dental radiography meets challenge to classify the dents into the proper class which useful for forensic and biomedical application. This paper proposed a novel method of classification and numbering on posterior dental radiography using support vector machine (SVM) with mesiodistal neck detection. In this method we developed SVM using a nouvelle feature with mesiodistal neck teeth. This feature was used to solve the problem in the dental image which suffered with completeness of whole part of teeth (crown-root). Preprocessing for enhancements included morphological operation, contrast adaptive, and tresholding. Every tooth has been assigned according to universal dental numbering and classified as their sequence order. Our system achieved classification precision of 90 %. This approach is robust and optimal for solving the problem of dental classification.

Original language	English
Title of host publication	6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
Pages	432-435
Number of pages	4
DOIs	https://doi.org/10.1109/SCIS-ISIS.2012.6505362
Publication status	Published - 2012
Event	2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe, Japan Duration: 20 Nov 2012 → 24 Nov 2012

Publication series

Name	6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012

Conference

Conference	2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
Country/Territory	Japan
City	Kobe
Period	20/11/12 → 24/11/12

Keywords

Image processing
Mesiodistal
Morphological filtering
Support Vector Machine
Teeth Numberin
dental

Access to Document

10.1109/SCIS-ISIS.2012.6505362

Cite this

Arifin, A. Z., Hadi, M., Yuniarti, A., Khotimah, W., Yudhi, A., & Astuti, E. R. (2012). Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection. In 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 (pp. 432-435). Article 6505362 (6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012). https://doi.org/10.1109/SCIS-ISIS.2012.6505362

Arifin, A. Z. ; Hadi, M. ; Yuniarti, A. et al. / Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection. 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012. 2012. pp. 432-435 (6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012).

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title = "Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection",

abstract = "Dental radiography meets challenge to classify the dents into the proper class which useful for forensic and biomedical application. This paper proposed a novel method of classification and numbering on posterior dental radiography using support vector machine (SVM) with mesiodistal neck detection. In this method we developed SVM using a nouvelle feature with mesiodistal neck teeth. This feature was used to solve the problem in the dental image which suffered with completeness of whole part of teeth (crown-root). Preprocessing for enhancements included morphological operation, contrast adaptive, and tresholding. Every tooth has been assigned according to universal dental numbering and classified as their sequence order. Our system achieved classification precision of 90 %. This approach is robust and optimal for solving the problem of dental classification.",

keywords = "Image processing, Mesiodistal, Morphological filtering, Support Vector Machine, Teeth Numberin, dental",

author = "Arifin, {A. Z.} and M. Hadi and A. Yuniarti and W. Khotimah and A. Yudhi and Astuti, {E. R.}",

note = "Funding Information: ACKNOWLEDGMENTS This work was supported by the Collegiate Scientific Program “Basic Research in the Natural Sciences and the Humanities in the Higher School: Universities of Russia”, grant no. 015.06.01.07.; 2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 ; Conference date: 20-11-2012 Through 24-11-2012",

year = "2012",

doi = "10.1109/SCIS-ISIS.2012.6505362",

language = "English",

isbn = "9781467327428",

series = "6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012",

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booktitle = "6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012",

}

Arifin, AZ, Hadi, M, Yuniarti, A, Khotimah, W, Yudhi, A & Astuti, ER 2012, Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection. in 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012., 6505362, 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012, pp. 432-435, 2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012, Kobe, Japan, 20/11/12. https://doi.org/10.1109/SCIS-ISIS.2012.6505362

Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection. / Arifin, A. Z.; Hadi, M.; Yuniarti, A. et al.
6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012. 2012. p. 432-435 6505362 (6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection

AU - Arifin, A. Z.

AU - Hadi, M.

AU - Yuniarti, A.

AU - Khotimah, W.

AU - Yudhi, A.

AU - Astuti, E. R.

N1 - Funding Information: ACKNOWLEDGMENTS This work was supported by the Collegiate Scientific Program “Basic Research in the Natural Sciences and the Humanities in the Higher School: Universities of Russia”, grant no. 015.06.01.07.

PY - 2012

Y1 - 2012

N2 - Dental radiography meets challenge to classify the dents into the proper class which useful for forensic and biomedical application. This paper proposed a novel method of classification and numbering on posterior dental radiography using support vector machine (SVM) with mesiodistal neck detection. In this method we developed SVM using a nouvelle feature with mesiodistal neck teeth. This feature was used to solve the problem in the dental image which suffered with completeness of whole part of teeth (crown-root). Preprocessing for enhancements included morphological operation, contrast adaptive, and tresholding. Every tooth has been assigned according to universal dental numbering and classified as their sequence order. Our system achieved classification precision of 90 %. This approach is robust and optimal for solving the problem of dental classification.

AB - Dental radiography meets challenge to classify the dents into the proper class which useful for forensic and biomedical application. This paper proposed a novel method of classification and numbering on posterior dental radiography using support vector machine (SVM) with mesiodistal neck detection. In this method we developed SVM using a nouvelle feature with mesiodistal neck teeth. This feature was used to solve the problem in the dental image which suffered with completeness of whole part of teeth (crown-root). Preprocessing for enhancements included morphological operation, contrast adaptive, and tresholding. Every tooth has been assigned according to universal dental numbering and classified as their sequence order. Our system achieved classification precision of 90 %. This approach is robust and optimal for solving the problem of dental classification.

KW - Image processing

KW - Mesiodistal

KW - Morphological filtering

KW - Support Vector Machine

KW - Teeth Numberin

KW - dental

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DO - 10.1109/SCIS-ISIS.2012.6505362

M3 - Conference contribution

AN - SCOPUS:84877824568

SN - 9781467327428

T3 - 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012

SP - 432

EP - 435

BT - 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012

T2 - 2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012

Y2 - 20 November 2012 through 24 November 2012

ER -

Arifin AZ, Hadi M, Yuniarti A, Khotimah W, Yudhi A, Astuti ER. Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection. In 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012. 2012. p. 432-435. 6505362. (6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012). doi: 10.1109/SCIS-ISIS.2012.6505362

Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection

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