International Journal of Soft Computing
ISSN: OnlineISSN: Print 1816-9503
Abstract
An entirely automatic procedure for the classification of cerebral tissues from Magnetic Resonance Nuclear imaging (MRN) 3D of the head are described in this study. This procedure doesn`t make any assumption nor on the number of classes nor on the shape of the density. Indeed, this last is estimated by a non parametric method, it is about the method of the Parzen`s Kernel. A new objective function is proposed to improve the FCM algorithm by the addition of one term of entropy aiming to maximize the number of good ordering. A supplementary correction is operated by a probabilistic procedure said of fuzzy relaxation including the probabilities of the neighboring points. The validation of the algorithm is made on simulated data and on real cerebral imaging RMN.
How to cite this article:
Nabila Ferahta , Abdelouahab Moussaoui , Khier Benmahammed and Victor Chen . New Fuzzy Clustering Algorithm Applied to Rmn Image Segmentation.
DOI: https://doi.org/10.36478/ijscomp.2006.137.142
URL: https://www.makhillpublications.co/view-article/1816-9503/ijscomp.2006.137.142