**5. Discussion**

Medical image analysis has become very important in the diagnosis of mild Alzheimer's disease in recent years [3]. But the important point is that from the way of analyzing medical images, we can determine the most effective channel for recording brain signals. 3D segmentation of MRI images further helps researchers diagnose Alzheimer's disease and obtain important information [7]. And in 3D images, the most appropriate direction in the image is effective in determining the appropriate features. Determining the degree of atrophy of MRI images is an effective method for early detection of Alzheimer's disease. Also, assessing the degree of asymmetry in both the right and left hemispheres and analyzing volumetric mismatch can differentiate between mild and severe Alzheimer's disease [7]. The degree of asymmetry

## *EEG and MRI Processing for Alzheimer's Diseases DOI: http://dx.doi.org/10.5772/intechopen.107162*

in the left and right hemispheres should be determined by the degree of atrophy and the ratio of the volume of gray matter to the volume of white matter. Using statistical features of signal and obtaining temporal information and using spatial features of MRI images is an effective method for the more accurate evaluation of Alzheimer's disease [8]. The statistical properties of the signal are temporal in nature and the statistical properties of the image are spatial in nature. Cortical atrophy means the gradual destruction of the nerve cells that make up the upper regions of the brain, specifically the structures found in the cerebral cortex, mostly due to a reduction or loss of oxygen and nutrients in these areas. There are several methods for examining the Medial temporal lobe, the accuracy of which is not clear [9]. However, this condition is more suitable for mild patients. Longitudinal T1-weighted MRI studies are another effective way to distinguish mild Alzheimer's patients from healthy ones [10]. But this feature has better results in severe patients to differentiate with mild patients. Also, extracting the appropriate characteristics and deciding on the classification in this field are among the issues to be considered.
