Abstract In this paper, we propose an efficient algorithm, the ACC-REG, to automatically extract intrinsic key characteristics on hippocampal mesh surfaces and hence compute an accurate registration mapping between them. Given a pair of hippocampal surface mesh, the proposed algorithm constructs the eigen-graphs, an intrinsic feature on the surface, on each surface as its representative. The eigen-graphs are then calibrated along the longitudinal direction of the hippocampal surfaces. Accurately corresponded intrinsic characteristics on each hippocampus can thus be extracted. As a result, the two surfaces can be registered with improved accuracy and low computation cost. Experiments on ADNI data demonstrate the effectiveness of the proposed ACC-REG model over existing methods.

中文翻译：

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自动特征校准配准 (ACC-REG)：使用特征图的海马表面配准

摘要 在本文中，我们提出了一种有效的算法 ACC-REG，以自动提取海马网格表面的内在关键特征，从而计算它们之间的准确配准映射。给定一对海马表面网格，所提出的算法构建特征图，即表面上的内在特征，在每个表面上作为其代表。然后沿着海马表面的纵向校准特征图。因此可以提取每个海马体上准确对应的内在特征。结果，可以以提高的精度和低的计算成本来配准这两个表面。ADNI 数据的实验证明了所提出的 ACC-REG 模型相对于现有方法的有效性。