CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Proposed Method for Tumour Segmentation in Brain MRI

by Harman Kataria, Alka Jindal
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 12
Year of Publication: 2012
Authors: Harman Kataria, Alka Jindal
10.5120/7676-0972

Harman Kataria, Alka Jindal . A Proposed Method for Tumour Segmentation in Brain MRI. International Journal of Computer Applications. 49, 12 ( July 2012), 1-5. DOI=10.5120/7676-0972

@article{ 10.5120/7676-0972,
author = { Harman Kataria, Alka Jindal },
title = { A Proposed Method for Tumour Segmentation in Brain MRI },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 12 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number12/7676-0972/ },
doi = { 10.5120/7676-0972 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:46:04.200869+05:30
%A Harman Kataria
%A Alka Jindal
%T A Proposed Method for Tumour Segmentation in Brain MRI
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 12
%P 1-5
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper deals with efficient medical image segmentation. The proposed method uses more than one scaling parameters such as sigma and epsilon. The proposed method reduces the number of iteration and tales less computational time than the original method. Comparison between original and proposed method is illustrated with the help of graph. It is possible to apply the proposed method to 2d as well as 3d images.

References
  1. Smitha Sunil Kumaran Nair and K. Revathy, "Quantitative analysis of brain tissues from Magnetic resonance images" IEEE International Conference on Digital Image Processing, 2009.
  2. V. Caselles, R. Kimmel, and G. Sapiro,"Geodesic active contour",Int. J. Comput. Vis, vol. 22, pp. 61-79, 1997.
  3. A. Vasilevskiy and K. Siddiqi, "Flux-maximizing geometric flows," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 24, no. 12, pp. 1565-1578, Dec. 2002.
  4. T. Chan and L. Vese," Active contour without edges," IEEE trans Image Process. , vol. 10, no. 2, pp 266-277, Feb. 2001.
  5. C. Xu and J. L. Prince, "Snakes, shapes, and gradient vector flow,"IEEE Trans. Image Process. , vol. 7, no. 3, pp. 359-369,Mar. 1998.
  6. Jia Di, Yang Jin-Zhu, Zhang Yi-Fei. "An Efficient Modified Level Set Method For Brain Tissue Segmentation", IEEE International Conference on Information and Automation june 2010.
  7. Shawn Lankton, Allen Tannenbaum, "Localizing Region-Based Active Contours," IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 17, NO. 11, NOVEMBER 2008.
  8. Harman Kataria and Alka Jindal, " Brain MRI: Region based segmentation techniques" IJCST Vol. 3, Iss ue 1, Jan. - March 2012 ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print)
  9. Chunming Li ,Chiu-Yen Kao and John C. Gore,"Minimization of Region-Scalable Fitting Energy for Image Segmentation",IEEE Trans. On Image Processing, vol. 17,n0. 10,October 2008.
  10. L. Vese and T. Chan, "A multiphase level set framework for image segmentation using the Mumford and Shah model, "Int. J. Comput. Vis. ,vol. 50, pp. 271–293, 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Active Contour Segmentation Intensity Inhomogenity Magnetic Resonance Image (MRI)

Powered by PhDFocusTM