Comprehensive segmentation of deep grey subcortical nuclei leveraging white-matter nulled contrast

Motivation: Lack of tools for comprehensive and complete segmentation of deep grey nuclei Goal(s): A robust method for segmentation of thalamic nuclei, basal ganglia, claustrum, amygdala, hippocamus, and ventricles from structural T1 MRI data at conventional field strengths Approach: We leverage the improved contrast of white-matter-nulled imaging by using the recently proposed Histogram-based Polynomial Synthesis (HIPS) to synthesize WMn-like images from standard T1 and then use a multi-atlas segmentation with joint label fusion Results: The method worked robustly on all field strengths (1.5/3/7) and Dice coefficients for almost all structures were comparable or higher than state-of-the-art. Impact: This method facilitates careful investigation of the role of deep grey nuclei by enabling the use of conventional T1 data from large public databases, which has not been possible, hitherto, due to lack of robust segmentation tools.