CFP last date
20 December 2024
Reseach Article

Clustering based Segmentation Approach to Detect Brain Tumor from MRI Scan

by Karishma Sheikh, Vidya Sutar, Silkesha Thigale
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 118 - Number 8
Year of Publication: 2015
Authors: Karishma Sheikh, Vidya Sutar, Silkesha Thigale
10.5120/20768-3224

Karishma Sheikh, Vidya Sutar, Silkesha Thigale . Clustering based Segmentation Approach to Detect Brain Tumor from MRI Scan. International Journal of Computer Applications. 118, 8 ( May 2015), 36-39. DOI=10.5120/20768-3224

@article{ 10.5120/20768-3224,
author = { Karishma Sheikh, Vidya Sutar, Silkesha Thigale },
title = { Clustering based Segmentation Approach to Detect Brain Tumor from MRI Scan },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 118 },
number = { 8 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 36-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume118/number8/20768-3224/ },
doi = { 10.5120/20768-3224 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:01:10.529041+05:30
%A Karishma Sheikh
%A Vidya Sutar
%A Silkesha Thigale
%T Clustering based Segmentation Approach to Detect Brain Tumor from MRI Scan
%J International Journal of Computer Applications
%@ 0975-8887
%V 118
%N 8
%P 36-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To detect the tumor in the brain is very important task but the major problem occurred is that its very time consuming. We provide an approach towards the automation of this process in this paper. We take magnetic resonance images of the brain as a input and attempt to calculated the position and the size of the tumor. Each pixel in each slice will be processed to detect the tumor. All the process used is automatic and independent from users capability demonstration of the experiment that methods can successfully achieve segmentation for MRI to help pathologist distinguish exactly size and region.

References
  1. Meiyan Huang,Wei Yang, YaoWu, Jun Jiang,Wufan Chen, Senior Member, IEEE, and Qianjin Feng?, Member, IEEE, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 61, NO. 10, OCTOBER 2014
  2. R. Manikandan, G. S. Monolisa and K. Saranya, A Cluster Based Segmentation of Magnetic Resonance Images for Brain Tumor Detection, Middle-East Journal of Scientific Research 14 (5): 669-672, 2013
  3. Atiq Islam, Syed M. S. Reza, and Khan M. Iftekharuddin?, Senior Member, IEEE, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 60, NO. 11, NOVEMBER 2013
  4. Sahar Ghanavati1, Junning Li1, Ting Liu1, Paul S. Babyn2, Wendy Doda2,GeorgeLampropoulos11 AUG Signals Ltd. , Toronto, ON. , Canada2 Hospital for Sick Children, Department of Medical Imaging, University of Toronto, ON. , Canada,2012
  5. Matthew C. Clark, Lawrence O. Hall,* Member, IEEE, Dmitry B. Goldgof, Senior Member, IEEE,Robert Velthuizen, Associate Member, IEEE, F. Reed Murtagh, and Martin S. Silbiger, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 17, NO. 2, APRIL 1998
  6. J. selvakumar, A. Lakshmi, T. Arivoli Brain Tumor Segmentation and Its Area Calculation in Brain MR Imagesusing K-Mean Clustering and Fuzzy C-Mean Algorithm.
  7. Ming-Ni Wu1, Chia-Chen Lin2, Chin-Chen Chang13 Brain Tumor Detection Using Color-Based K-Means Clustering Segmentation.
  8. Abduljawad A. Amory, Rachid Sammouda A Content Based Retrieval Method For MR Brain Images.
  9. Sahar Ghanavati1, Junning Li1, Ting Liu1, Paul S. Babyn2, Wendy Doda2,GeorgeLampropoulos1. AUTOMATIC BRAIN TUMOR DETECTION IN MAGNETIC RESONANCE IMAGES.
  10. Matthew C. Clark, Lawrence O. Hall,* Member, IEEE, Dmitry B. Goldgof, Senior Member, IEEE,Robert Velthuizen, Associate Member, IEEE, F. Reed Murtagh, and Martin S. Silbiger. "Automatic Tumor Segmentation Using Knowledge-Based Techniques".
  11. Hossam M. Moftah, Aboul Ella Hassanien, and Mohamoud Shoman. " 3D Brain Tumor SegmentationScheme using K-mean Clustering and Connected Component Labeling Algorithms".
  12. Dina Aboul Dahab1, Samy S. A. Ghoniemy2, Gamal M. Selim3 Automated Brain Tumor Detection and Identification Using Image Processing and Probabilistic Neural Network Techniques.
  13. Akram, M. U. Dept. of Comput. & Software Eng. , Bahria Univ. , Islamabad, Pakistan Usman, A. Computer aided system for brain tumor detection and segmentation.
Index Terms

Computer Science
Information Sciences

Keywords

biomedical k-means algorithm magnetic resonance images nervous system spinal cord skull.