Graph wedgelets are a novel tool for the fast decomposition of images in geometrically meaningful, wedge-shaped subregions. In this work, we study the usage of graph wedgelets as a promising splitting method in a split-and-merge segmentation scheme for Magnetic Resonance Imaging. We combine adaptive wedgelet splits of MRI images with a simple and classical merging strategy for subregions and obtain in this way an efficient and robust segmentation of diagnostic-relevant subdomains in MRI data.
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