Implementation of segmentation methods for the diagnosis and prognosis of mild cognitive impairment and Alzheimer disease

Abstract

Alzheimer's disease (AD) is the most common form of dementia affecting seniors age 65 and over. When AD is suspected, the diagnosis is usually confirmed with behavioural assessments and cognitive tests, often followed by a brain scan. Advanced medical imaging is a good tool to predict conversion from prodromal stages (mild cognitive impairment) to Alzheimer's disease. Since volumetric MRI can detect changes in the size of brain regions, measuring those regions that atrophy during the progress of Alzheimer's disease can help the neurologist in his diagnostic. In the present investigation, we present an automatic tool that reads volumetric MRI and performs 2-dimensional (volume slices) and volumetric segmentation methods in order to segment gray matter, white matter and cerebrospinal fluid (CSF). We used the MRI data sets database from the Open Access Series of Imaging Studies (OASIS). © IOP Publishing Ltd.