Nonlinear Flows for Displacement Correction and Applications in Tomography
Guozhi Dong, Otmar Scherzer
TL;DR
This paper introduces nonlinear evolution equations derived from non-convex energy functionals to correct displacement errors in imaging data, with applications demonstrated in tomographical data correction.
Contribution
It presents a novel class of nonlinear filtering flows based on non-convex energies for displacement correction in imaging, with experimental validation in tomography.
Findings
Effective correction of angular perturbations demonstrated
Nonlinear flows improve image accuracy in tomography
Theoretical properties of the filtering flows analyzed
Abstract
In this paper we derive nonlinear evolution equations associated with a class of non-convex energy functionals which can be used for correcting displacement errors in imaging data. We study properties of these filtering flows and provide experiments for correcting angular perturbations in tomographical data.
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Taxonomy
TopicsMedical Imaging Techniques and Applications · Numerical methods in inverse problems · Advanced X-ray and CT Imaging