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Metamorphosis of images in reproducing kernel Hilbert spaces

机译:再现核希尔伯特空间中图像的变形

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摘要

Metamorphosis is a method for diffeomorphic matching of shapes, with many potential applications for anatomical shape comparison in medical imagery, a problem which is central to the field of computational anatomy. An important tool for the practical application of metamorphosis is a numerical method based on shooting from the initial momentum, as this would enable the use of statistical methods based on this momentum, as well as the estimation of templates from hyper-templates using morphing. In this paper we introduce a shooting method, in the particular case of morphing images that lie in a reproducing kernel Hilbert space (RKHS). We derive the relevant shooting equations from a Lagrangian frame of reference, present the details of the numerical approach, and illustrate the method through morphing of some simple images.
机译:变形是一种用于形状的形态匹配的方法,在医学图像中具有许多在解剖形状比较中的潜在应用,这是计算解剖学领域的核心问题。实际应用变形的重要工具是基于从初始动量射击的数值方法,因为这将使得能够使用基于该动量的统计方法,以及使用变形从超模板估计模板。在本文中,我们介绍了一种拍摄方法,特别是对位于可再生内核希尔伯特空间(RKHS)中的图像进行变形的情况下。我们从拉格朗日参考系中得出相关的射击方程,给出数值方法的细节,并通过对一些简单图像进行变形来说明该方法。

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