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Brain Tumor Segmentation using K-Means Clustering Algorithm


Author : Sanghamitra T. Kamble and M. R. Rathod

Pages : 1521-1524
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Abstract

Since image segmentation is a classic inverse problem which consist of achieving a compact region based description of the image scene by decomposing it into meaningful or spatially regions sharing similar attributes. Tumor is nothing but uncontrolled growth of tissues in any part of the body. Tumors are of different types and they have different treatments. The K-means algorithm is an iterative technique that is used to partition an image into K clusters. In developed countries most research show that the number of people who have brain tumors were died due to inaccurate detection of tumor .CT scan or MRI is directed into intracranial cavity produces a complete image of brain and this image is visually examined for detection.

Keywords: Magnetic Resonance Imaging(MRI),Brain tumor, K-means, CT (Computerized tomoghraphy) scan, Thresholding, Image segmentation

Article published in International Journal of Current Engineering and Technology, Vol.5, No.3 (June-2015)

 

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