Segmentation Of Brain Mr Images For Tumor Area And Size Detection By Using Of Clustering Algorithm

1536 Words7 Pages
SEGMENTATION OF BRAIN MR IMAGES FOR TUMOR AREA AND SIZE DETECTION BY USING OF CLUSTERING ALGORITHM
Shinu Sadeyone1 Assistant professor (Sathyabama University, Chennai)
S.Freeda2 Assistant professor (A.C.T engineering college, Chngalpattu) 1shinusedayone@gmail.com. 2freeda27@gmail.com.

Abstract- There are different types of tumors are available. Astrocytoma is the most common type of tumor (30% of all brain tumor) and is usually a malignant one. Astrocytoma can be subdivided into four grades. Each grade has its own characteristics and unique treatment. In the event that any wrong treatment is given to these evaluations that prompts passing. So finding the position and shape of tumor is very important for the further treatment. The proposed system of this paper is to find the exact position and shape of the tumor cells. That helps the physician for further treatment. In the proposed system, it consists of four modules (i) Pre-processing, (ii) Segmentation of brain in MR Images,(iii) Quality extraction and (iv) Inexact reasoning. Preprocessing is carried out by sifting. Segmentation is carried out by cutting edge both K-means and Fuzzy C-means calculations. Quality extraction is by thresholding. Finally, Approximate reasoning method to recognize the tumor shape and position in MRI image. If the tumor is a mass in shape then k-means algorithm is enough to extract it from brain cells. Suppose if it is a malignant (spread over the brain) one then the Fuzzy C-means algorithm

More about Segmentation Of Brain Mr Images For Tumor Area And Size Detection By Using Of Clustering Algorithm

Get Access