@article{MAKHILLIJSC20061220756,
    title = {New Fuzzy Clustering Algorithm Applied to Rmn Image Segmentation},
    journal = {International Journal of Soft Computing},
    volume = {1},
    number = {2},
    pages = {137-142},
    year = {2006},
    issn = {1816-9503},
    doi = {ijscomp.2006.137.142},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2006.137.142},
    author = {Nabila Ferahta,Abdelouahab Moussaoui,Khier Benmahammed and},
    keywords = {automatic classification,Clustering,SKIZ,markov fields,image segmentation,Maximum Posterior Marginal (MPM)},
    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.}
    }