Abstract:
This study is an effort to study brain - white matter (WM ), gray matter (GM ), cerebrospinal fluid (CSF) -
in M RI images which shows normal appearance if the patients were normal or had convulsion, through
computerized analysis. The main objective of this study was to identify brain tissue as normal and
abnormal “convulsion” pediatric using textural analysis. The textural features were extracted from the
whole M RI image using a window of 3×3pixel wide, where the first order statistics (mean, standard
deviation, Coefficient of variation etc...) were extracted using one pixel interlace. The features in the
window were classified as GM or WM or CSF as well as normal or abnormal using K-means and
discriminate analysis. The images were collected from M RI brain scans for 41 patients presented for
examination in the period from July 2014 to December 2014, 5 patients is control and 36 patients as cases
underwent epilepsy protocol and T1, T2 and FLAIR images obtained. Segmentation analysis and ratios
are compared between structures of the both diseased and control groups. the classification technique
were adopted as a method of pattern identification the image into normal or elliptic classes. Linear
discriminate analysis using steps wise were used to classify the WM , GM and CSF into the predefined
classes normal and convulsion one. The result of this classification showed that the white matter of the
convulsion cases showed a high classification accuracy of 99.5% and demarked as separate class from the
rest of the class’s weather it normal or abnormal. In conclusion the white matter of the convulsion cases
texturally were very different from the normal one while from visual perception point of view they appear
similar
