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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 2 Issue 6, 2011.
Abstract: The fusion of information is a domain of research in full effervescence these last years. Because of increasing of the diversity techniques of images acquisitions, the applications of medical images segmentation, in which we are interested, necessitate most of the time to carry out the fusion of various data sources to have information with high quality. In this paper we propose a system of data fusion through the framework of the possibility theory adapted for the segmentation of MR images. The fusion process is divided into three steps : fuzzy tissue maps are first computed on all images using Fuzzy C- Means algorithm. Fusion is then achieved for all tissues with a fusion operator. Applications on a brain model show very promising results on simulated data and a great concordance between the true segmentation and the proposed system.
Lamiche Chaabane and Moussaoui Abdelouahab, “ Improvement of Brain Tissue Segmentation Using Information Fusion Approach” International Journal of Advanced Computer Science and Applications(IJACSA), 2(6), 2011. http://dx.doi.org/10.14569/IJACSA.2011.020612
@article{Chaabane2011,
title = { Improvement of Brain Tissue Segmentation Using Information Fusion Approach},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2011.020612},
url = {http://dx.doi.org/10.14569/IJACSA.2011.020612},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {6},
author = {Lamiche Chaabane and Moussaoui Abdelouahab}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.