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Brain Tumor Segmentation And Detection
Subject area: Science,Engineering and Technology · Area of research: Electronics and Communication Engineering
Abstract
Tumor is an uncontrolled growth of tissues in any part of the body and they have different characteristics and different treatments. As brain tumor is inherently serious and life threatening because number of individuals who died due to the fact of inaccurate detection. Generally, MRI produces complete image of brain. This image is visually examined for detection and diagnosis. This paper describes the computer aided method for segmentation of tumor using K-means clustering, PCA and SVM for classification of tumor. This method allows the detection of tumor tissue with accuracy comparable to manual segmentation. In addition, it also reduces time for analysis. At the end of the process the exact position and the shape of the tumor is determined.
Keywords
Brain tumor, MRI, K-means, DWT, PCA, SVM.
References
[1] C. L. Devasena and M. Hemalatha, “Efficient computer aided diagnosis of abnormal parts detection in magnetic resonance images using hybrid abnormality detection algorithm,” Central European Journal of Computer Science, vol. 3, no. 3, pp. 117– 128, 2013.
[2] E. Dandil, M. Cakiroglu, Z. Eksi, “Computer-aided diagnosis of malign and benign brain tumors on MR images,” ICT Innovations 2014, pp. 157–166, 2015.
[3] M. P. Arakeri and G. R. M. Reddy, “Computer- aided diagnosis system for tissue characterization of brain tumor on magnetic resonance images,” Signal, Image and Video Processing, vol. 9, no. 2, pp. 409–425, 2015.
[4] J. Cheng, X. Chen, H. Yang, and M. Leng, “An enhanced k- means algorithm using agglomerative hierarchical clustering strategy,” International Conference on Automatic Control and Artificial Intelligence (ACAI 2012). pp. 407–410, 2012.
[5] K. Shil, F. P. Polly, M. A. Hossain, M. S. Ifthekhar, M. N. Uddin, and Y. M. Jang “An Improved Brain Tumor Detection and Classification Mechanism”.
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How to cite this paper
@article{1702094,
author = {B. V. Sathish Kumar, Utla Naga Durga Sreenija, Venkata Sri Vyshnavi Nerella, Thanusha Lakshmi Munagala, Tulabandula Veda Sri Teja},
title = {Brain Tumor Segmentation And Detection},
journal = {Iconic Research And Engineering Journals},
year = {2020},
volume = {3},
number = {10},
pages = {40-43},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1702094.pdf},
abstract = {Tumor is an uncontrolled growth of tissues in any part of the body and they have different characteristics and different treatments. As brain tumor is inherently serious and life threatening because number of individuals who died due to the fact of inaccurate detection. Generally, MRI produces complete image of brain. This image is visually examined for detection and diagnosis. This paper describes the computer aided method for segmentation of tumor using K-means clustering, PCA and SVM for classification of tumor. This method allows the detection of tumor tissue with accuracy comparable to manual segmentation. In addition, it also reduces time for analysis. At the end of the process the exact position and the shape of the tumor is determined.},
keywords = {Brain tumor, MRI, K-means, DWT, PCA, SVM.},
month = {April},
}