Abstract
Alzheimer’s disease (AD) is a degenerative neuronal brain disorder resulting in memory loss, skills, and cognitive changes. The disorder’s primary diagnostic tests are defined as total brain atrophy and hippocampal atrophy. Early diagnosis is significant, and automatic systems design is necessary for this disorder. Potential biomarkers for AD are described using a hippocampal magnetic resonance imaging volumetry system with certain limitations. For the definite identification of the hippocampus region, pre-processing of the 3D MRI images of AD is necessary. The filtering and histogram-based pre-processing techniques enhance the region of interest, which helps in effectively segmenting the biomarker, the hippocampus. The median and eight histogram clippings are defined to be 98% efficient pre-processing techniques with the comparison of image quality parameters and statistical analysis. Thus an algorithm for pre-processing of the 3D MRI images of stages of AD is designed for the further process of identification.
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