%0 Journal Article
%A Aganj, Iman
%A Iglesias, Juan Eugenio
%A Reuter, Martin
%A Sabuncu, Mert Rory
%A Fischl, Bruce
%T Mid-space-independent deformable image registration.
%J NeuroImage
%V 152
%@ 1053-8119
%C Orlando, Fla.
%I Academic Press
%M DZNE-2020-05620
%P 158-170
%D 2017
%X Aligning 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 mathematical definition of the mid-space. In particular, the set of possible solutions is typically restricted by the constraints that are enforced on the transformations to prevent the mid-space from drifting too far from the native image spaces. The use of an implicit atlas has been proposed as an approach to mid-space image registration. In this work, we show that when the atlas is aligned to each image in the native image space, the data term of implicit-atlas-based deformable registration is inherently independent of the mid-space. In addition, we show that the regularization term can be reformulated independently of the mid-space as well. We derive a new symmetric cost function that only depends on the transformation morphing the images to each other, rather than to the atlas. This eliminates the need for anti-drift constraints, thereby expanding the space of allowable deformations. We provide an implementation scheme for the proposed framework, and validate it through diffeomorphic registration experiments on brain magnetic resonance images.
%K Algorithms
%K Atlases as Topic
%K Brain: anatomy & histology
%K Brain Mapping: methods
%K Female
%K Humans
%K Imaging, Three-Dimensional
%K Magnetic Resonance Imaging
%K Male
%K Middle Aged
%K Signal Processing, Computer-Assisted
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:28242316
%2 pmc:PMC5432428
%R 10.1016/j.neuroimage.2017.02.055
%U https://pub.dzne.de/record/139298