Accurate and automatic brainstem nuclei segmentation from MR images plays an important role in seeking for imaging-biomarkers of Parkinson’s disease (PD). To address the segmentation challenge from regular MR images, we propose a novel multi-atlas patch based label fusion method where we use hyper-graph technique to handle the low image contrast issue. Our proposed method is successfully applied to a set of MR images from PPMI (Parkinson’s Progression Markers Initiative) dataset, and we have achieved significant improvements in terms of segmentation accuracy compared to the state-of-the-art methods.
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