Early diagnosis and objective monitoring of disease progression are essential for the development of therapeutic strategies in Alzheimer's disease (AD). Current techniques are mainly based on semi-objective measures such as neuropsychological tests and a physician's magnetic resonance imaging (MRI) inspection. We have developed a computational method for automatic and unbiased assessment of the brain's state of atrophy from MRI. Sixty-eight high-resolution MRI scans were acquired from 25 AD patients (age: 69.8±7.5), 16 mild cognitive impairment (MCI) patients (67.6±9.1) and 27 control subjects (64.9±8.8). On the basis of the computations we were able to recognize MCI subjects with a sensitivity of 81% and a specificity of 80% in a group of MCIs and controls using a linear classifier. To date, comparable results have only been received by manual labelling or human inspection. Our calculations are light weighted and can be applied on usual workstations in everyday clinical practice. Each step can be understood and applied by the physicians, independent of their computer knowledge. The applied image analysis process produces visual maps of atrophic changes as intermediate steps of the calculations. These can be helpful for the physician during inspection of the brain. The proposed analysis has the potential to improve AD diagnosis and treatment, especially in early its stages, and could also be used to monitor disease progression in therapeutic trials.