A Survey of Alzheimer’s disease using Fuzzy Neural Network
Abstract
Alzheimer disease is one of the most common diseases in the aging population, ranking as the fourth most common cause of death and it is a progressive neurodegenerative disorder characterized by the gradual onset of dementia. Magnetic resonance imaging (MRI) is a preferred neuro imaging examination for Alzheimer disease diagnosis. It allows accurate 3-dimensional (3D) volume measurement of brain structures. The primary role of MRI in the diagnosis of Alzheimer disease is the assessment of volume change in characteristic locations. The diagnosis should be made on the basis of two features:
mesial temporal lobe atrophy and temporoparietal cortical atrophy.
Computer implementations increased the accuracy and performance of detecting undergoing changes in affected brain areas. It uses Image Segmentation and integrating of its algorithms provides simpler guidance for the diagnosis process. This paper provides a survey of existing techniques of image segmentation and a comparison of the K-means and neuro-fuzzy algorithms are also given.