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Metamorphosis of Images in Reproducing Kernel Hilbert Spaces

2014/09/23 by Casey L. Richardson, Richardson, Casey L, Laurent Younès +1
Computer Science · Engineering · Mathematics · #3D Shape Modeling and Analysis #FOS: Mathematics #Medical Image Segmentation Techniques #Morphological variations and asymmetry #Optimization and Control (math.OC)

paper · pdf · doi:10.48550/arxiv.1409.6573

openalex publication_date 2014/09/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

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