Alzheimer's detection at early stage using local measures on MRI: A comparative study on local measures

Alzheimer's disease (AD) is a Dementia among older people which causes neurological degradation. Mild Cognitive Impairment [1] (MCI) is a condition which could progress and then become AD but is not explicitly visible in one's behavior. This paper presents a strategic approach for recognizing MCI at early stage using Magnetic Resonance Imaging (MRI). Initially Grey Matter (GM) is segmented and Local Patterns is extracted from it This study explores the ability of Local Patterns to classify between Normal, Mild Cognitive Impairment (MCI) and AD. This study is based on the fact that GM volume loss in the MCI group compared to Normal Aging and AD is greater and reports the classification accuracy of various Local Patterns. Local Graph Structure shows greater accuracy compared to other Local Patterns.