Nabila Ferahta  , Abdelouahab Moussaoui  , Khier Benmahammed  , Victor Chen  , 
    New Fuzzy Clustering Algorithm Applied to Rmn Image Segmentation,
    International Journal of Soft Computing,
    Volume 1,Issue 2,
    2006,
    Pages 137-142,
    ISSN 1816-9503,
    ijscomp.2006.137.142,
    (https://makhillpublications.co/view-article.php?doi=ijscomp.2006.137.142)
    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.
    Keywords: automatic classification;Clustering;SKIZ;markov fields;image segmentation;Maximum Posterior Marginal (MPM)