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IntroductionImage is an array or matrix of square pixels arranged in columns and rows.Image processing involves treating the image as a two dimensional signal and then applying standard signal techniques.The build up of extra cells often forms a mass of tissue called a growth or tumor.The brain tumor affects CSF and causes stroke.Problem statementDoctors use many tests to diagnose a brain tumor to find out the type of tumor and spread of tumor to others parts of body.Most effective and common tools to determine the tumor is use of MRI, CT PET scan.To determine the type of tumor , a sample of the tumor tissue is taken by biopsy or by removing the part or entire tumor. This tissue is given for test.In most cases, the stage cannot be determined unless until biopsy is done.Literature Survey

Existing SystemThe existing system is based on:ThresholdRegion growingIn threshold based segmentation the image is considered to have only two values either black or white.The regional growing method ignored the spatial characteristics.Proposed systemThe proposed method consist of mainly 4 parts:PreprocessingSegmentation using k-means and fuzzy c-meansFeature extractionApproximate reasoningDesign

ModulesPreprocessingSegmentation by k-means and fuzzy c-means Feature extractionApproximate reasoningConclusionThere are different types of tumors available. They may be mass in the brain or malignant over the brain. This method scans the RGB or grayscale, converts the image into binary image by binarization technique and detects the edge of tumor pixels in the binary image. Also, it calculates the size of the tumor by calculating the number of white pixels (digit 0) in binary image. The stage of the tumor is based on the area of tumor.References[1] mohammed sabbih hamoud al-tamimi, ghazali sulong, tumor brain detection through mr images: a review of literature, Journal of Theoretical and Applied Information Technology 20th April 2014. Vol. 62 No.2 2005 - 2014 JATIT & LLS.

[2] A.R.Kavitha, Dr.C.Chellamuthu, Ms.Kavin Rupa, An Efficient Approach for Brain Tumour Detection Based on Modified Region Growing and Network in MRI Images,Information Forensics and Security, IEEE Transactions on, Vol.9 (2), May 2012.

[3]R.B.Dubey, M.Hanmandlu, Sr.Member, Shantaram Vasikarla, Evaluationof Three Methods for MRI Brain Tumor segmentation, IEEE Digital Object Identifier: 10.1109/ITNG.2011.92,2011

[4] Shaheen Ahmed, Khan M.Iftekharuddin, Efficacy of Texture, Shape and Intensity Feature Fusion for Posterior Fossa Tumor Segmentation InMRI, IEEE Vol (2), pag: 206-13, Mar 2011.

[5] Ali Gooya, George Biros Christos Davatzikos, An EM Algorithm for BrainTumor ImagesRegistration: A Tumor Growth Modling Based Approach, IEEE,Vol 2, pag: 375-90, May 2010.Thank you