Brain Disease Classification using Different Wavelet Analysis for Support Vector Machine (SVM)

Muhammad Fahrur Rozi, Dian Candra Rini Novitasari, Putroue Keumala Intan

2018

Abstract

The brain is one of the vital organs, some diseases attack the brains aregliomas and brain cancer. Glioma is a type of tumor in the human brain, while brain cancer is a condition of abnormal cell growth in the brain. The danger of these two diseases often causes death. Both diseases have different treatment methods. Therefore, it is necessary to classify MRI images accurately. Extraction of features in images can affect the classification process. In this study, we compare the best feature extraction methods that can be used in brain MRI, wavelet decomposition and wavelet texture analysis. In this study, to test the accuracy of the two methods is using an SV Mas classification method. The results show the wavelet texture analysis had better results than using wavelet decomposition. This statement is indicated by the results of accuracy using wavelet texture analysis of 82.14% compared to the accuracy of using wavelet decomposition of 75%.

Paper Citation

in Harvard Style

Rozi M., Novitasari D. and Intan P. (2018). Brain Disease Classification using Different Wavelet Analysis for Support Vector Machine (SVM).In Proceedings of the International Conference on Mathematics and Islam - Volume 1: ICMIs, ISBN 978-989-758-407-7, pages 460-465. DOI: 10.5220/0008523704600465

in Bibtex Style

@conference{icmis18,
author={Muhammad Fahrur Rozi and Dian Candra Rini Novitasari and Putroue Keumala Intan},
title={Brain Disease Classification using Different Wavelet Analysis for Support Vector Machine (SVM)},
booktitle={Proceedings of the International Conference on Mathematics and Islam - Volume 1: ICMIs,},
year={2018},
pages={460-465},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008523704600465},
isbn={978-989-758-407-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Mathematics and Islam - Volume 1: ICMIs,
TI - Brain Disease Classification using Different Wavelet Analysis for Support Vector Machine (SVM)
SN - 978-989-758-407-7
AU - Rozi M.
AU - Novitasari D.
AU - Intan P.
PY - 2018
SP - 460
EP - 465
DO - 10.5220/0008523704600465