Classification of Brain Tumor using Neural Network

Abstract

Due to uncontrolled cell devision within the brain abnormal tissue growth will occur this is known as the brain tumor. There are two types of brain tumors that is malignant(cancerous) and benign(non cancerous).Benign tumor increases with age but not malignant. About 25% of the total cancer deaths are due to this brain tumor.Hence,detection of brain tumor is a serious concern in the current scenario. Magnetic resonance imaging (MRI) is the widely used technique to detect Brain tumor. While diagnosing large amount of data by an expert the computational complexity and time consuming is more and it is prone to errors. To investigate an automated system which consists of two stages here? In the first stage, segment the tumor area from brain MRI using Multiracial analysis with RBF classifier. There are three features are considered that is intensity,fractal dimension and gray level co-occurrence matrix(GLCM).Here second stage classifies the segmented tumor area into benign or malignant using one of the best features (GLCM) in the wavelet domain along with a best classifier.

Authors and Affiliations

Lekshmi Senan , Ratheesh. I

Keywords

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  • EP ID EP22475
  • DOI -
  • Views 213
  • Downloads 5

How To Cite

Lekshmi Senan, Ratheesh. I (2016). Classification of Brain Tumor using Neural Network. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(8), -. https://europub.co.uk/articles/-A-22475