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Automated segmentation and volumetric analysis of brain components on MR imaging

As the world population has been growing old, the incidence of several brain diseases, including dementia, has risen. As a consequence, a greater demand for automated segmentation methods and volumetric analysis of the brain structure and its components has increased. This work is based on the use of image processing algorithms and previous knowledge statistical models for automated segmentation over 386 magnetic resonance exams. We analyze brain components considering two different image subsets: non-demented and demented individuals. Our results demonstrate gray and white matter loss, and CSF enlargement with aging.