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A New Matching Algorithm Between Trees of Shapes and Its Application to Brain Tumor Segmentation

机译:一种新的形状与脑肿瘤分割应用的新匹配算法及其应用

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Many approaches exist to compute the distance between two trees in pattern recognition. These trees can be structures with or without values on their nodes or edges. However, none of these distances take into account the shapes possibly associated to the nodes of the tree. For this reason, we propose in this paper a new distance between two trees of shapes based on the Hausdorff distance. This distance allows us to make inexact tree matching and to compute what we call residual forests, representing where two trees differ. We will also see that thanks to these residual forests, we can obtain good preliminary results in matter of brain tumor segmentation. This segmentation not only provides a segmentation but also the tree of shapes corresponding to the segmentation and its depth map.
机译:存在许多方法来计算模式识别中的两棵树之间的距离。 这些树木可以是有或没有它们的节点或边缘的结构的结构。 但是,这些距离都不考虑到可能与树的节点相关联的形状。 出于这个原因,我们在本文中提出了基于Hausdorff距离的两棵树的两棵树之间的新距离。 这个距离允许我们做出不精确的树匹配,并计算我们所谓的残余森林,代表两棵树不同的地方。 我们还将认为,由于这些残留的森林,我们可以获得脑肿瘤细分的良好初步结果。 该分割不仅提供了分割,而且还提供了与分段及其深度图对应的形状树。

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