An optimal control approach for the registration of image time-series

Abstract

This paper discusses an optimal control approach for the registration of image time-series (growth modeling). It combines and augments work on an optimal control formulation to optical flow with theory from large-displacement diffeomorphic image registration. The unification of the two viewpoints leads to (i) a more efficient computation of the gradient of the optimization problem, (ii) an easier numerical implementation, and (iii) an intuitive interpretation of the adjoint equation underlying the optimization problem. Further, a novel formulation for the unbiased estimation of image correspondences across time is proposed.

Publication
Proceedings of the 48th IEEE Conference on Decision and Control, CDC 2009, combined withe the 28th Chinese Control Conference, December 16-18, 2009, Shanghai, China
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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