Template Estimation for Large Database: A Diffeomorphic Iterative Centroid Method Using Currents
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Abstract
Computing a template in the Large Deformation Diffeomorphic Metric Mapping framework is a key step for the shape analysis of anatomical structures, but can lead to very computationally expensive algorithms in the case of large databases. We present an iterative method which quickly provides a centroid of the population in shape space. This centroid can be used as a rough template estimate or as initialization for template estimation methods.
Keywords
Large Database Reproduce Kernel Hilbert Space Shape Space Standard Initialization Computational Anatomy
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