MRI Images Thresholding for Alzheimer Detection

摘要

More than 55 illnesses are associated with the development of dementia and Alzheimer's disease (AD) is the most prevalent form. Vascular dementia (VD ) is the second most common fo rm of dementia. Current diagnosis of Alzheimer disease (Alzheimer's disease) is made by clinical, neuropsychological, and neuroimaging assessments. Magnetic resonance imaging (MRI) can be considered the preferred neuroimaging examination for Alzheimer disease because it allows for accurate measurement of brain structures, especially the size of the hippocampus and related regions. Image processing techniques has been used for processing the (MRI) image. Image thresholding is an important concept, both in the area of objects segmentation and recognition. It has been widely used due to the simplicity of implementation and speed of time execution. Many thresholding techniques have been proposed in the literature. The aim of this paper is to provide formula and their implementation to threshold images using Between-Class Variance with a Mixture of Gamma Distributions. The algorithms will be described by given their steps, and applications. Experimental results are presented to show good results on segmentation of (MRI) image