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Computational and Mathematical Methods in Medicine
Volume 2014 (2014), Article ID 712783, 10 pages
Research Article

A Hybrid Approach of Using Symmetry Technique for Brain Tumor Segmentation

1Department of Computer Science, COMSATS Institute of Information Technology, Abbottabad, Pakistan
2Department of Information Science, College of Computing Sciences and Engineering, Kuwait University, Kuwait

Received 24 June 2013; Revised 30 December 2013; Accepted 9 January 2014; Published 9 March 2014

Academic Editor: Seungryong Cho

Copyright © 2014 Mubbashar Saddique et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Tumor and related abnormalities are a major cause of disability and death worldwide. Magnetic resonance imaging (MRI) is a superior modality due to its noninvasiveness and high quality images of both the soft tissues and bones. In this paper we present two hybrid segmentation techniques and their results are compared with well-recognized techniques in this area. The first technique is based on symmetry and we call it a hybrid algorithm using symmetry and active contour (HASA). In HASA, we take refection image, calculate the difference image, and then apply the active contour on the difference image to segment the tumor. To avoid unimportant segmented regions, we improve the results by proposing an enhancement in the form of the second technique, EHASA. In EHASA, we also take reflection of the original image, calculate the difference image, and then change this image into a binary image. This binary image is mapped onto the original image followed by the application of active contouring to segment the tumor region.