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Abstract #2234

Split-and-Merge Segmentation in Magnetic Resonance Imaging Based on Graph Wedgelets

Wolfgang Erb1
1Dipartimento di Matematica "Tullio Levi-Civita", University of Padova, Padova, Italy


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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