Automated segmentation of gray and white matter regions in brain MRI images for computer aided diagnosis of neurodegenerative diseases

Abstract

This work presents a framework for neurological disease prediction and decision making for patients of cognitive impairment, dementia, or Alzheimer's disease based on automatic segmentation of gray and white matter regions as anatomical features in brain MRI images. Changes in the size or volume of these regions can be correlated to changes in cerebral structure in patients with Alzheimer's, dementia, cognitive impairment, or other neurological disorders. Specifically, the thickness of the cortex plays an important role in determining the severity level of dementia or cognitive impairment. The work herein presents a method using the segmentation of gray and white matter from the brain MRI slices of the patient as part of the development of a software platform based computational tool for aiding neurologists in assessing anatomical and functional changes in cerebral structure from brain MRI scans of neurological patients. The aforementioned tool can be implemented as a software package that can be installed in the computational platforms in the neurology department or division of hospitals. In its final implementation and deployment, this tool would predict neurological disease type and severity after automatically processing the brain MRI or CT images with the above-mentioned algorithms, and displaying the highlighted gray and white matter regions in the brain CT or MRI images.