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Crack Detection on Inner Tunnel Surface Using Image Processing Read chapter Read first chapter

2021 | OriginalPaper | Chapter

G.V Black Classification of Dental Caries Using CNN

Authors : Prerna Singh, Priti Sehgal

Published in: Progress in Advanced Computing and Intelligent Engineering

Publisher: Springer Singapore

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Abstract

Dental caries is one of the most predominant pathologies in the world. Early detection of dental caries leads to the prevention of tooth decay. According to G.V Black classification model dental caries can be classified into six classes (Class I–Class VI) based on the location of caries. The proposed work classifies caries infected tooth based on G.V black classification using deep convolution network architecture (DCNN). In the proposed approach, feature extraction of the preprocessed images is done using Local Ternary Pattern (LTP) and feature reduction is done using Principal Component Analysis (PCA). The pretrained models used in the study are AlexNet architecture and GoogleNet architecture. AlexNet is 8 layer DCNN and classifies the tooth with an accuracy of 93%, 90% sensitivity and 92% specificity. GoogleNet is a 22 layer DCNN and classifies with an accuracy of 94%, 91% sensitivity and 93% specificity.

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Literature
1.
Datta S, Chaki, N (2015) Detection of dental caries lesion at early stage based on image analysis technique. In: 2015 IEEE international conference on computer graphics, vision and information security (CGVIS). IEEE, pp 89–93
2.
Naebi M, Saberi E, Risbaf Fakour S, Naebi A, Hosseini Tabatabaei S, Ansari Moghadam S, Azimi H (2016) Detection of carious lesions and restorations using particle swarm optimization algorithm. Int. J. Dentis.
3.
Singh P, Sehgal P (2017) Automated caries detection based on Radon transformation and DCT. In: 2017 8th international conference on computing communication and networking technologies (ICCCNT). IEEE, pp 1–6
4.
Prajapati SA, Nagaraj R, Mitra S (2017) Classification of dental diseases using CNN and transfer learning. In: 2017 5th international symposium on computational and business intelligence (ISCBI). IEEE, pp 70–74
5.
Miki Y, Muramatsu C, Hayashi T, Zhou X, Hara T, Katsumata A, Fujita H (2017) Classification of teeth in cone-beam CT using deep convolutional neural network. Comput Biol Med 80:24–29CrossRef
6.
Lee JH, Kim DH, Jeong SN, Choi SH (2018) Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. J Dent 77:106–111CrossRef
7.
Salehi HS, Mahdian M, Murshid MM, Judex S, Tadinada A (2019) Deep learning-based quantitative analysis of dental caries using optical coherence tomography: an ex vivo study. In: Lasers in Dentistry XXV, vol 10857. International Society for Optics and Photonics, p 108570H
8.
Singh P, Sehgal P (2020) Decision support system for black classification of dental images using GIST descriptor. Presented at 3rd International Conference on Advanced Computing and Intelligent Engineering (ICACIE). Proceeding to be published in Advances in Intelligent System and Computing(AISC) series of Springer
9.
Tan X, Triggs B (2010) Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE Trans Image Process 19(6):1635–1650MathSciNetCrossRef
10.
Phillips PJ, Flynn PJ, Scruggs T, Bowyer KW, Chang J, Hoffman K, Marques J, Min J, Worek W (2005, June). Overview of the face recognition grand challenge. In: 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR’05), vol 1. IEEE, pp 947–954
11.
Hu W, Huang Y, Wei L, Zhang F, Li H (2015) Deep convolutional neural networks for hyperspectral image classification. J Sens
12.
Krizhevsky A, Sutskever I, Hinton GE (2012) ImageNet classification with deep convolutional neural network. In: Advances in neural information processing systems, vol 25. NIPS, pp. 1106–1114
13.
Zhou B, Khosla A, Lapedriza A, Torralba A, Oliva A (2016) Places: an image database for deep scene understanding
14.
Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V, Rabinovich A (2014) Going deeper with convolutions. Computing research repository
Metadata
Title
G.V Black Classification of Dental Caries Using CNN
Authors
Prerna Singh
Priti Sehgal
Copyright Year
2021
Publisher
Springer Singapore
Book
Progress in Advanced Computing and Intelligent Engineering

Print ISBN: 978-981-15-6583-0

Electronic ISBN: 978-981-15-6584-7

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-6584-7_11