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@ARTICLE{Aganj:139298,
      author       = {Aganj, Iman and Iglesias, Juan Eugenio and Reuter, Martin
                      and Sabuncu, Mert Rory and Fischl, Bruce},
      title        = {{M}id-space-independent deformable image registration.},
      journal      = {NeuroImage},
      volume       = {152},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {DZNE-2020-05620},
      pages        = {158-170},
      year         = {2017},
      abstract     = {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.},
      keywords     = {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},
      cin          = {AG Reuter},
      ddc          = {610},
      cid          = {I:(DE-2719)1040310},
      pnm          = {345 - Population Studies and Genetics (POF3-345)},
      pid          = {G:(DE-HGF)POF3-345},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:28242316},
      pmc          = {pmc:PMC5432428},
      doi          = {10.1016/j.neuroimage.2017.02.055},
      url          = {https://pub.dzne.de/record/139298},
}