• Dr.B.Shadaksharappa
• Reji Thomas
• Nikhil Kumar
• Subhasish Mohapatra
• Rishabh Srivatsava

Images play a vital role in every field that make the problem easier to understand. Image processing techniques are most widely used in medical imaging to identify the affected area through MRI scan.Image processing is used to detect and identify the inner most portion of the human body. Computer aided detection of abnormal growth of tissues is primarily motivated by the necessity of achieving maximum possible accuracy. Manual segmentation of these abnormal tissues cannot be compared with modern day's high speed computing machines which enable us to visually observe the volume and location of unwanted tissues. A well known segmentation problem within MRI is the task of labeling the tissue type which include White Matter (WM), Grey Matter (GM), Cerebrospinal Fluid (CSF) and sometimes pathological tissues like tumor etc. This paper describes an efficient method for automatic brain tumor segmentation for the extraction of tumor tissues from MRI images. In this method segmentation is carried out using K-means clustering algorithm for better performance. This enhances the tumor boundaries more and is very fast when compared to many other clustering algorithms. Using K-Means Clustering Algorithm, we can filter the brain tumor of an image. The algorithm is been used on different images of the brain detected with tumor and show the desired output.

Image Segmentation, Clustering Pixels,MRI Images,K-Means Clustering, Detecting Tumors

"Diagnosis Of Brain Tumors Using Intelligent Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.312-315, May-2019, Available :http://www.jetir.org/papers/JETIRCJ06071.pdf

"Diagnosis Of Brain Tumors Using Intelligent Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp312-315, May-2019, Available at : http://www.jetir.org/papers/JETIRCJ06071.pdf