News Updates Thursday 26th Dec 2024 :
  • Welcome to INPRESSCO, world's leading publishers, We have served more than 10000+ authors
  • Articles are invited in engineering, science, technology, management, industrial engg, biotechnology etc.
  • Paper submission is open. Submit online or at editor.ijcet@inpressco.com
  • Our journals are indexed in NAAS, University of Regensburg Germany, Google Scholar, Cross Ref etc.
  • DOI is given to all articles

Brain Tumor Segmentation using K-Means Clustering Algorithm


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

Pages : 1521-1524
Download PDF
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)

 

Call for Papers
  1. IJCET- Current Issue
  2. Issues are published in Feb, April, June, Aug, Oct and Dec
  3. DOI is given to all articles
  • Inpressco Google Scholar
  • Inpressco Science Central
  • Inpressco Global impact factor
  • Inpressco aap

International Press corporation is licensed under a Creative Commons Attribution-Non Commercial NoDerivs 3.0 Unported License
©2010-2023 INPRESSCO® All Rights Reserved