Metamorphic Geodesic Regression

Abstract

We propose a metamorphic geodesic regression approach approximating spatial transformations for image time-series while simultaneously accounting for intensity changes. Such changes occur for example in magnetic resonance imaging (MRI) studies of the developing brain due to myelination. To simplify computations we propose an approximate metamorphic geodesic regression formulation that only requires pairwise computations of image metamorphoses. The approximated solution is an appropriately weighted average of initial momenta. To obtain initial momenta reliably, we develop a shooting method for image metamorphosis.

Publication
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012 - 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III
Yi Hong
Yi Hong
Ph.D. in Computer Science
Marc Niethammer
Marc Niethammer
Professor of Computer Science

My research interests include image registration, image segmentation, shape analysis, machine learning, and biomedical applications.

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