The basal ganglia, thalamus and brainstem are affected by movement disorders and contain key targets for functional neurosurgery. Targeting however is based on indirect coordinates originally derived from pneumoencephalograms! 3D Fast Gray Matter Acquisition T1 Inversion Recovery (FGATIR) can directly visualize potential targeted structures (e.g. dentatorubrothalamic tract), but is signal-starved in clinically-feasible acquisitions. We developed a convolutional neural network to improve FGATIR quality. Expert rater assessment suggested this CNN improved contrast resolution of individual structures and overall clinical image quality of 1-average data to the level of 4-averages. This could further enable investigations of functional neurosurgery for movement disorders.