Automatic and consistent hippocampus segmentation from longitudinal infant brain MR image sequences is crucial for the measurement and analysis of its growth trajectory during early brain developing stage. To achieve this goal, we propose to use the longitudinal hypergraph method for joint learning the MR images from multiple acquisition time-points. We apply the proposed method to segment hippocampus from infant brain MR dataset which contains five time-points from 2 weeks to 12 months of age. According to the experimental results, our method outperforms other state-of-the-art label fusion methods in terms of both segmentation accuracy and consistency.
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