Abstract: In the aim of providing sophisticated applications and getting benefits from the advantageous properties of agents, designing agent-based and multi-agent systems has become an important issue that received further consideration from many application domains. Towards the same goal, this work gathered three different research fields; image segmentation, fuzzy clustering and multi-agent systems (MAS); and furnished a MAS for MR brain image segmentation that is based on a fast and robust FCM (FRFCM) algorithm. The proposed MAS was tested, as well as the sequential version of the FRFCM algorithm and the standard FCM, on simulated and real normal brains. The experimental results were valuable in both segmentation accuracy and running times point of views.

Hanane Barrah, Abdeljabbar Cherkaoui and Driss Sarsri, “MAS based on a Fast and Robust FCM Algorithm for MR Brain Image Segmentation” International Journal of Advanced Computer Science and Applications(IJACSA), 7(7), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070726

@article{Barrah2016,
title = {MAS based on a Fast and Robust FCM Algorithm for MR Brain Image Segmentation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070726},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070726},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {7},
author = {Hanane Barrah and Abdeljabbar Cherkaoui and Driss Sarsri}
}