Mid-Space-Independent Symmetric Data Term for Pairwise Deformable Image Registration.

Med Image Comput Comput Assist Interv

Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.

Published: October 2015

Aligning a pair of images in a mid-space is a common approach to ensuring that deformable image registration is symmetric - that it does not depend on the arbitrary ordering of the input images. The results are, however, generally dependent on the choice of the mid-space. In particular, the set of possible solutions is typically affected by the constraints that are enforced on the two transformations (that deform the two images), which are to prevent the mid-space from drifting too far from the native image spaces. The use of an implicit atlas has been proposed to define the mid-space for pairwise registration. In this work, we show that by aligning the atlas to each image in the native image space, implicit-atlas-based pairwise registration can be made independent of the mid-space, thereby eliminating the need for anti-drift constraints. We derive a new symmetric cost function that only depends on a single transformation morphing one image to the other, and validate it through diffeomorphic registration experiments on brain magnetic resonance images.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4732576PMC
http://dx.doi.org/10.1007/978-3-319-24571-3_32DOI Listing

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