Mild Cognitive Impairment (MCI) is a transitional state between normal aging and Alzheimer’s disease (AD). Patients with sever AD cant do their usuall activities and needs long time care. This will force a lot of cost to patient’s family and community, while in MCI state can prevent disease progress. This can be a strong reason why diagnosis is so important in MCI state. Alzheimer’s is common form of dementia and known by memory loss in patients. As disease progresses patient’s ability of doing daily acitivity is decreasing. Researchers commonly pay attention to brain regions which are connected to memory functionality.Hippocampus, temporal and frontal gyrals are regions which are examined a lot by theme. Results had been shown that in AD, Hippocampus atrophy is much more than normal aging. Also gyral shrinkage and ventricle enlargement which cause more CSF in brain, are significant in AD. On the other hand in MCI state, these changes are not so significant and distinguishing a MCI patient from a normal aging adult is difficult. For this reason, Machine Learning (ML) methods came to help researchers to Fourty subjects including 20 healthy subject and 20 MCI were selected from Sina and Nour hospitals in Isfahan. These subjects meet criteria for participating in this experiment. MR images with 1.2mm slice thickness were taken from all subjects. These images was processed through Freesurfer software and sevberal brain features such as region volumes, thickness and area was extracted. AS all extracted features can’t Keywords Mild Cognitive Impairment, Demetia, Machine Learning, ltr"
