@article{MAKHILLRJAS201611109898,
    title = {Classificstion of Brain MRI Images Using Classifier Techniques
Supported by Genetic and Fuzzy C-Means},
    journal = {Research Journal of Applied Sciences},
    volume = {11},
    number = {10},
    pages = {1137-1142},
    year = {2016},
    issn = {1815-932x},
    doi = {rjasci.2016.1137.1142},
    url = {https://makhillpublications.co/view-article.php?issn=1815-932x&doi=rjasci.2016.1137.1142},
    author = {Noor Kadhum,Asraa Abdullah and},
    keywords = {Classification,GLCM,K-nearest,fuzzy C-means,genetic algorithm,K-means,neural network},
    abstract = {Computer techniques play important role in medical fields, especially in the classification and disease diagnoses. In this study, Brain MRI is classified using many techniques. Back propagation neural network, K-nearest and K-means used for classifying these images into normal and abnormal after clustering images using fuzzy C-means and minimizing the extracted features by GLCM using genetic algorithm. The system shows high efficiency through practical experiments that proves that the accuracy of system is reached to 100% through back propagation neural network.}
    }