Automated Computer Differential Classification in Parkinsonian Syndromes via Pattern Analysis on MRI

These results demonstrate that a classification approach based on quantitative parameters of three-dimensional hindbrain morphology extracted automatically from T1w magnetic resonance imaging has the potential to assist in the differential diagnosis of IPD versus PSP and MSA with high accuracy, therefore reducing the initial clinical error rate.