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Research Article |

Classification & Feature extraction of Brain tumor from MRI Images using Modified ANN Approach

Author(s): Harendra Singh and Roop Singh Solanki*

Published In : International Journal of Electrical and Electronics Research (IJEER)        volume 9, Issue 2

Publisher : FOREX Publication

Published : 30 June 2021

e-ISSN : 2347-470X

Page(s) : 10-15

DOI: https://doi.org/10.37391/IJEER.090202

Abstract

In this research paper, a new modified approach is proposed for brain tumor classification as well as feature extraction from Magnetic Resonance Imaging (MRI) after pre-processing of the images. The discrete wavelet transformation (DWT) technique is used for feature extraction from MRI images and Artificial Neural Network (ANN) is used for the classification of the type of tumor according to extracted features. Mean, Standard deviation, Variance, Entropy, Skewness, Homogeneity, Contrast, Correlation are the main features used to classify the type of tumor. The proposed model can give a better result in comparison with other available techniques in less computational time as well as a high degree of accuracy. The training and testing accuracies of the proposed model are 100% and 98.20% with a 98.70 % degree of precision respectively.

Keywords: Magnetic Resonance Imaging (MRI), Discrete Wavelet Transformation (DWT), Image Pre-Processing & Filtering, Artificial Neural Network (ANN).




Harendra Singh, Research Scholar, Department of Electronics & Communication, MVN University, Palwal, Haryana, India

Roop Singh Solanki*, Research Scholar, Department of Electronics & Communication, Uttarakhand Technical University, Dehradun, India; Email: roopsolanki@gmail.com

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Harendra Singh and Roop Singh Solanki (2021), Classification & Feature extraction of Brain tumor from MRI Images using Modified ANN Approach. IJEER 9(2), 10-15. DOI: 10.37391/IJEER.090202.