Using the Navier-Cauchy equation for motion estimation in dynamic imaging

TL;DR

This paper demonstrates that incorporating deformation fields from the Navier-Cauchy equation into dynamic tomography reconstruction can effectively reduce motion artifacts caused by elastic deformations like respiratory motion.

Contribution

It introduces a novel approach that uses the Navier-Cauchy PDE to model and compensate for elastic deformations in dynamic imaging reconstruction.

Findings

Deformation fields from Navier-Cauchy equation improve image quality.

Method reduces motion artifacts in simulated CT data.

Proof-of-concept validated with numerical examples.

Abstract

Tomographic image reconstruction is well understood if the specimen being studied is stationary during data acquisition. However, if this specimen changes during the measuring process, standard reconstruction techniques can lead to severe motion artefacts in the computed images. Solving a dynamic reconstruction problem therefore requires to model and incorporate suitable information on the dynamics in the reconstruction step to compensate for the motion. Many dynamic processes can be described by partial differential equations which thus could serve as additional information for the purpose of motion compensation. In this article, we consider the Navier-Cauchy equation which characterizes small elastic deformations and serves, for instance, as a model for respiratory motion. Our goal is to provide a proof-of-concept that by incorporating the deformation fields provided by this PDE, one can reduce the respective motion artefacts in the reconstructed image. To this end, we solve the Navier-Cauchy equation prior to the image reconstruction step using suitable initial and boundary data. Then, the thus computed deformation fields are incorporated into an analytic dynamic reconstruction method to compute an image of the unknown interior structure. The feasibility is illustrated with numerical examples from computerized tomography.