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Optimized Approach for Brain Tumor Detection from Brain MRI


Affiliations
1 V.L.B. Janakiammal College of Engineering and Technology, Coimbatore, India
     

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This paper presents an optimized technique for Brain tumor detection from MR Images. The proposed system consists of two phases, namely, feature extraction and detection. In two steps the efficient techniques are used to increase the accuracy of the system so that to reduce the number of false detection. In feature extraction the texture features are extracted which shows better performance in various diagnoses. The classifiers detect the timorous image based on features. Here the classifier fusion system is used which is formed using more number of classifiers. The K-nn, SVM and ANN classifiers are used in classifier fusion system. The results show that this system has higher efficiency when compared to other system.

Keywords

MRI, Texture, GLCM, Classifier Fusion, K-NN Classifier, ANN, SVM.
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  • Optimized Approach for Brain Tumor Detection from Brain MRI

Abstract Views: 267  |  PDF Views: 3

Authors

S. Suresh
V.L.B. Janakiammal College of Engineering and Technology, Coimbatore, India

Abstract


This paper presents an optimized technique for Brain tumor detection from MR Images. The proposed system consists of two phases, namely, feature extraction and detection. In two steps the efficient techniques are used to increase the accuracy of the system so that to reduce the number of false detection. In feature extraction the texture features are extracted which shows better performance in various diagnoses. The classifiers detect the timorous image based on features. Here the classifier fusion system is used which is formed using more number of classifiers. The K-nn, SVM and ANN classifiers are used in classifier fusion system. The results show that this system has higher efficiency when compared to other system.

Keywords


MRI, Texture, GLCM, Classifier Fusion, K-NN Classifier, ANN, SVM.



DOI: https://doi.org/10.36039/ciitaas%2F3%2F6%2F2011%2F106962.282-286