Abstract
Regularization is used in deformable image registration to encourage plausible displacement fields, and significantly impacts the derived correspondences. Sliding motion, such as that between the lungs and chest wall and between the abdominal organs, complicates registration because many regularizations are global smoothness constraints that produce errors at object boundaries. We present locally adaptive regularizations that handle sliding objects with locally planar and tubular geometries. These regularizations allow discontinuities to develop in the displacement field at sliding interfaces and increase the independence with which regions surrounding distinct geometric structures can behave. Validation is performed by registering inhale and exhale abdominal computed tomography (CT) images and artificial images of a sliding tube. The sliding registration methods produce more realistic correspondences that may better reflect the underlying physical motion, while performing as well as the diffusive regularization with respect to image match.
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Pace, D.F., Niethammer, M., Aylward, S.R. (2012). Sliding Geometries in Deformable Image Registration. In: Yoshida, H., Sakas, G., Linguraru, M.G. (eds) Abdominal Imaging. Computational and Clinical Applications. ABD-MICCAI 2011. Lecture Notes in Computer Science, vol 7029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28557-8_18
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DOI: https://doi.org/10.1007/978-3-642-28557-8_18
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