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Research Journal of Pharmacy and Technology
Year : 2019, Volume : 12, Issue : 5
First page : ( 2171) Last page : ( 2174)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2019.00361.5

Classification of Radiolucency in Dental X-Ray Image

Britto Carl Jordan1,*, Dr. Anita H.B.2

1MCA, PG Scholar, Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, Karnataka

2Associate Professor, Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, Karnataka, anita.hb@christuniversity.in

*Corresponding Author E-mail: carljordanbritto@gmail.com

Online published on 8 August, 2019.

Abstract

Health is the greatest gift to any human being. Growth of the nation depends on the health of every individual. To maintain health and hygiene, a human being must eat good food. For eating healthy food teeth plays an important role. The teeth being a small part of the body plays a very critical part in digestion. Many times due to time constraints patient cannot go to the hospital at right time or wants to get a second opinion. So, in this aspect, the proposed system is created to diagnose the status of the tooth automatically. The anticipated system takes x-ray images as input and classifies the output as a category of radiolucency that it falls under. The classification of the tooth is done by using Multi-Layer Perceptron (MLP), SMO, KNN. Features are extracted using both, Spatial and Frequency domain. Classification is done using Weka tool.

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Keywords

Multi-Layer Perceptron (MLP), Random Forest, Sequential Minimal Optimization (SMO), Gray Level Co-occurrence Matrix (GLCM), Fast Fourier Transform (FFT).

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