and automated segmentation of substantia nigra (SN), the subthalamic nucleus
(STN), and the red nucleus (RN) in quantitative susceptibility mapping (QSM)
images has great significance in many neuroimaging studies. In the present
study, we present a novel segmentation method by using convolution neural
networks (CNN) to produce automated segmentations of the SN, STN, and RN. The
model was validated on manual segmentations from 21 healthy subjects. Average
Dice scores were 0.82±0.02 for the SN, 0.70±0.07
for the STN and 0.85±0.04 for the RN.