In this study, a decision making method was developed for determination epileptogenicity in mesial temporal lobe epilepsy (mTLE) patients using different neuroimaging markers including hippocampal volume, and FLAIR (Fluid Attenuated Inversion Recovery) intensity and MD (Mean Diffusivity) value in hippocampus, FA (Fractional anisotropy) in posteroinferior cingulum, and FA in crus of fornix from MRI images of T1, FLAIR, and DTI (diffusion tensor imaging). The aim of this study is to creating an automated classification algorithm using decision tree and random forest methods. Result of applied method detected essential rules for prediction of laterality in individual mTLE patients.
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