Template Estimation for Large Database: A Diffeomorphic Iterative Centroid Method Using Currents
نویسندگان
چکیده
Computing a template in the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework is a key step for the study of large databases of anatomical surfaces, but can lead to very computationally expensive algorithms in the case of large databases. Here we present an iterative method to compute a better initialization for the template estimation method proposed in [1]. The method provides quickly a centroid of the population in shape space. Using this centroid as initialization for template estimation can save up to 72% of computation
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Diffeomorphic Iterative Centroid Methods for Template Estimation on Large Datasets
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