Template Estimation for Large Database: A Diffeomorphic Iterative Centroid Method Using Currents

Claire Cury 1 Joan Alexis Glaunès 2 Olivier Colliot 1
1 ARAMIS - Algorithms, models and methods for images and signals of the human brain
Inria Paris-Rocquencourt, UPMC - Université Pierre et Marie Curie - Paris 6, ICM - Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute
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.
Type de document :
Communication dans un congrès
Frank Nielsena and Frédéric Barbaresco. GSI 2013 - First International Conference Geometric Science of Information, Aug 2013, Paris, France. Springer, 8085, pp.103-111, 2013, Lecture Notes in Computer Science. <10.1007/978-3-642-40020-9_10>
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https://hal.archives-ouvertes.fr/hal-00857440
Contributeur : Joan Alexis Glaunès <>
Soumis le : mardi 3 septembre 2013 - 15:17:07
Dernière modification le : lundi 29 mai 2017 - 15:34:11

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Claire Cury, Joan Alexis Glaunès, Olivier Colliot. Template Estimation for Large Database: A Diffeomorphic Iterative Centroid Method Using Currents. Frank Nielsena and Frédéric Barbaresco. GSI 2013 - First International Conference Geometric Science of Information, Aug 2013, Paris, France. Springer, 8085, pp.103-111, 2013, Lecture Notes in Computer Science. <10.1007/978-3-642-40020-9_10>. <hal-00857440>

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