Discrimination between Alzheimer’s Disease, Mild Cognitive Impairment and Normal Aging Using ANN Based MR Brain Image Segmentation
Alzheimer’s disease (AD) is the most common cause of dementia among people aged 60 years and older. Mild Cognitive impairment (MCI) is a pre-dementia condition that has been shown to have a high likelihood of progression to AD. In this prospective study evaluate the accuracy of the GM and CSF volumetry to help distinguish between patients with AD and MCI and subjects with elderly controls. This study we explored the ability of BP-ANN identify the structural changes of Grey Matter (GM), White Matter (WM) and Cerebrospinal fluid (CSF) in different groups using real MR images. The proposed approach employs morphological operations used for skull stripping and gabor filter for feature extraction. In these results we report a statistically significant trend towards accelerated GM volume loss in the MCI group compared to the NCI and AD from the MCI. We report the results of the classification accuracies on both training and test images are up to 96%.
KeywordsAlzheimer’s disease Mild Cognitive Impairment No Cognitive impairment Artificial Neural network Magnetic Resonance Imaging
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