An Efficient Segmentation Technique for Mri Medical Images
M. Ganesh1, V. Palanisamy2
1M.Ganesh, ECE, Info Institute of Engineering, Coimbatore, India..
2V.Palanisamy, Principal, Info Institute of Engineering, Coimbatore, India
Manuscript received on October 01, 2012. | Revised Manuscript received on October 05, 2012. | Manuscript published on October 10, 2012. | PP: 70-73 | Volume-1 Issue-5 October 2012. | Retrieval Number: E0303091512 /2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image segmentation is a technique to locate certain objects or boundaries within an image. Image segmentation plays a crucial role in many medical imaging applications. There are many algorithms and techniques have been developed to solve image segmentation problems. Spectral pattern is not sufficient in high resolution image for image segmentation due to variability of spectral and structural information. Thus the spatial pattern or texture techniques are used. Thus we proposed an efficient image segmentation technique, in which we have used the concept of Adaptive Fuzzy C-Means Algorithm for segmentation of high resolution medical image. The proposed method is implemented in Matlab and verified using various kinds of high resolution medical images. The experimental results shows that the proposed image segmentation system is efficient than the existing segmentation systems.
Keywords: Image Segmentation, Adaptive Fuzzy C-Means Algorithm, Clustering, Gabor Filter, Morphological Operation.