There is a need of accurate imaging biomarkers of dopaminergic cell neurodegeneration to facilitate drug trials in Parkinson’s disease (PD). PD demonstrates neurodegenerative substantia nigra pars compacta (SNc) changes that can be detected efficiently using neuromelanin-sensitive MRI. Characterizing neuromelanin signal variations using manual SNc segmentation is an operator-dependent and time-consuming task. Hence, in this cross-sectional, observational, case-control study, we investigated neuromelanin SNc abnormalities in the early PD patients using convolutional neural network-based fully automatic segmentation of SNc. We found a highly significant difference in SNc volume and signal intensity between early PD and healthy volunteers.