G. Mahalakshmi1
, G. Heren Chellam2
Section:Research Paper, Product Type: Journal Paper
Volume-07 ,
Issue-08 , Page no. 16-20, Apr-2019
CrossRef-DOI:
https://doi.org/10.26438/ijcse/v7si8.1620
Online published on Apr 10, 2019
Copyright © G. Mahalakshmi, G. Heren Chellam . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: G. Mahalakshmi, G. Heren Chellam, “Segmentation and Classification of Brain Tumor MRI Images Using Support Vector Machine,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.08, pp.16-20, 2019.
MLA Style Citation: G. Mahalakshmi, G. Heren Chellam "Segmentation and Classification of Brain Tumor MRI Images Using Support Vector Machine." International Journal of Computer Sciences and Engineering 07.08 (2019): 16-20.
APA Style Citation: G. Mahalakshmi, G. Heren Chellam, (2019). Segmentation and Classification of Brain Tumor MRI Images Using Support Vector Machine. International Journal of Computer Sciences and Engineering, 07(08), 16-20.
BibTex Style Citation:
@article{Mahalakshmi_2019,
author = {G. Mahalakshmi, G. Heren Chellam},
title = {Segmentation and Classification of Brain Tumor MRI Images Using Support Vector Machine},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {07},
Issue = {08},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {16-20},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=908},
doi = {https://doi.org/10.26438/ijcse/v7i8.1620}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i8.1620}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=908
TI - Segmentation and Classification of Brain Tumor MRI Images Using Support Vector Machine
T2 - International Journal of Computer Sciences and Engineering
AU - G. Mahalakshmi, G. Heren Chellam
PY - 2019
DA - 2019/04/10
PB - IJCSE, Indore, INDIA
SP - 16-20
IS - 08
VL - 07
SN - 2347-2693
ER -
This paper proposes a set of algorithms which work for the better detection and classification of Brain Tumor. The MRI image based Brain Tumor analysis would efficiently deal with classification process for Brain Tumor analysis. There are three stages namely Feature Extraction, Feature Reduction and Classification. Feature Extraction and Feature Reduction using for two algorithms. There are Discrete Wavelet Transform (DWT) and Principle Component Analysis (PCA). The Features Extracted are Mean, Standard deviation, Kurtosis, Skewness, Entropy, Contrast, Variance, Smoothness, Correlation and Energy. The result is then given to Support Vector Machine (SVM) for tumor classification as Benign or Malignant.
Brain Tumor, Discrete Wavelet Transform (DWT), Principal Component Analysis (PCA), Support Vector Machine (SVM), Magnetic Resonance image (MRI).
[1] N. Varuna Shree T. N. R. Kumar “Detection and classification of brain tumor MRI images with using Discrete Wavelet Transform and probabilistic neural network”. Published online: 8 January 2018
[2] M.Rama Krishna, Fahmeeda, G.Daizy Florence and K.Sravani, “Brain Tumor Image Segmentation Based On Discrete Wavelet Transform and Support Vector Machine”, International Journal for Modern Trends in Science and Technology, Vol. 03, Special Issue 02, 2017, pp. 12-18.
[3] 1P. Kumar and 2B. Vijayakumar “Brain Tumor MRI Image of the process of Segmentation of Classification Using by Principle Analysis Component (PCA) and RBF Kernel Based Support Vector Machine (SVM)” Middle-East Journal of Scientific Research 23 (9): 2106-2116, 2015 ISS 1990-9233 © IDOSI Publications, 2015
