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3D statistical shape model building using consistent parameterization

 
: Kirschner, Matthias; Wesarg, Stefan

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Fulltext (PDF; )

Deserno, T.M. ; Gesellschaft für Informatik -GI-, Bonn:
Bildverarbeitung für die Medizin 2010 : Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 14. bis 16. März 2010 in Aachen
Berlin: Springer, 2010 (Informatik aktuell)
ISBN: 978-3-642-11967-5
ISSN: 1431-472X
ISSN: 1613-0073
pp.291-295
Workshop Bildverarbeitung für die Medizin (BVM) <13, 2010, Aachen>
English
Conference Paper, Electronic Publication
Fraunhofer IGD ()
point correspondence; surface parameterization; statistical shape model (SSM); image segmentation; 3D medical data; Forschungsgruppe Medical Computing (MECO)

Abstract
We propose a new correspondence optimisation algorithm for building 3D statistical shape models (SSMs) of genus-0 shapes. The main contribution of our work is the use of parameter space propagation to generate consistent spherical parameterisations of the training shapes. We present evaluation results for two data sets: A set of 30 liver shapes from different patients, and a set of 25 left ventricles covering the cardiac cycle of a single patient. Our evaluation shows that the use of parameter space propagation improves the robustness of correspondence optimisation algorithms and lead to fast convergence times.

: http://publica.fraunhofer.de/documents/N-131588.html