17 Aganj, Iman Iglesias, Juan Eugenio Reuter, Martin Sabuncu, Mert Rory Fischl, Bruce AG Reuter NeuroImage NeuroImage Academic Press Orlando, Fla. 1053-8119 10.1016/j.neuroimage.2017.02.055 English 158-170 152 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. PUB:(DE-HGF)16, ; 0, ; Algorithms Atlases as Topic Brain: anatomy & histology Brain Mapping: methods Female Humans Imaging, Three-Dimensional Magnetic Resonance Imaging Male Middle Aged Signal Processing, Computer-Assisted Journal Article 2017 DZNE-2020-05620 2017 pmc:PMC5432428 pmid:28242316 https://pub.dzne.de/record/139298 https://doi.org/10.1016/j.neuroimage.2017.02.055