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An Image Registration Framework for Discontinuous Mappings Along Cracks

机译:沿裂缝的不连续映射的图像登记框架

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摘要

A novel crack capable image registration framework is proposed. The approach is designed for registration problems suffering from cracks, gaps, or holes. The approach enables discontinuous transformation fields and also features an automatically computed crack indicator function and therefore does not require a pre-segmentation. The new approach is a generalization of the commonly used variational image registration approach. New contributions are an additional dissipation term in the overall energy, a proper balancing of different ingredients, and a joint optimization for both, the crack indicator function and the transformation. Results for histological serial sectioning of marmoset brain images demonstrate the potential of the approach and its superiority as compared to a standard registration.
机译:提出了一种新颖的裂缝能够的图像登记框架。 该方法专为患有裂缝,间隙或孔的注册问题而设计。 该方法使得不连续变换字段能够具有自动计算的裂缝指示符功能,因此不需要预分割。 新方法是常用的变分图像登记方法的概括。 新贡献是整体能量的额外耗散术语,不同成分的适当平衡,以及裂缝指示器功能和转化的联合优化。 Marmoset脑图像的组织序列切片的结果表明,与标准登记相比,方法的潜力及其优势。

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