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Establishing Local Correspondences towards Compact Representations of Anatomical Structures

机译:建立局部对应于解剖结构的紧凑表示

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摘要

Computer-aided diagnosis is often based on comparing a structure of interest with prior models. Such a comparison requires automatic techniques in determining prior models from a set of examples and establishing local correspondences between the structure and the model. In this paper we propose a variational technique for solving the correspondence problem. The proposed method integrates a powerful representation for shapes (implicit functions), a state-of-the-art criterion for global registration (mutual information) and an efficient technique to recover local correspondences (free form deformations) that guarantees one-to-one mapping. Local correspondences can then be used to build compact representations for a structure of interest according to a set of training examples. The registration and statistical modeling of Systolic Left Ventricle shapes in Ultrasonic images demonstrate the potential of the proposed technique.
机译:计算机辅助诊断通常基于将感兴趣的结构与先前的模型进行比较。这种比较需要自动技术来根据一组示例确定先前的模型,并在结构和模型之间建立局部对应关系。在本文中,我们提出了一种解决对应问题的变分技术。所提出的方法集成了强大的形状表示(隐式函数),最新的全局配准(相互信息)和有效的技术来恢复局部对应关系(自由形式变形),从而确保了一对一映射。然后,根据一组训练示例,可以使用局部对应关系来构建感兴趣结构的紧凑表示。超声图像中收缩期左心室形状的配准和统计建模证明了该技术的潜力。

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