Indirect Image Registration with Large Diffeomorphic Deformations (2017-06-13T00:00:00.000000Z)

TL;DR

The paper adapts the large deformation diffeomorphic metric mapping framework for image registration to the indirect setting where a template is registered against a target that is given through indirect noisy observations and proves that indirect image registration has solutions that are stable and converge as the data error tends so zero.

Abstract

The paper adapts the large deformation diffeomorphic metric mapping framework for image registration to the indirect setting where a template is registered against a target that is given through indirect noisy observations. The registration uses diffeomorphisms that transform the template through a (group) action. These diffeomorphisms are generated by solving a flow equation that is defined by a velocity field with certain regularity. The theoretical analysis includes a proof that indirect image registration has solutions (existence) that are stable and that converge as the data error tends so zero, so it becomes a well-defined regularization method. The paper concludes with examples of indirect image registration in 2D tomography with very sparse and/or highly noisy data.

Authors

Chong Chen

1 papers

O. Öktem

1 papers

TL;DR

Abstract

Authors

References75 items

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