2. Iman Aganj 1, Juan E. Iglesias 2, Martin Reuter 1,3, Mert R. Sabuncu 1,3, Bruce Fischl 1,3,4 1 Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA 2 Basque Center on Cognition, Brain and Language, San Sebastian, Spain 3 Computer Science and Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA 4 Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA

4. Mid-Space Lorenzen et al, MedIA’06; Avants et al, NI’04; Yang et al, PMB’08; Noblet et al, PRL’12; Lorenzi et al, NI’13; Ashburner et al, FN’13. Problem: Mid-space drift

5. Mid-Space Joshi et al, NI’04; Ma et al, NI’08; Hart et al, CVPR’09; Ashburner et al, FN’13. Data term:

6. Mid-Space Ma et al, NI’08. Analytical form for the atlas:

7. Mid-Space Ashburner et al, FN’13. Atlas-independent data term:

8. The proposed method. Mid-space-independent data term: No need for anti-drift constraints!

9. Comparison with the symmetrization data term: Christensen et al, TMI’01; Cachier & Rey, MICCAI’2000; Trouvé & Younes, ECCV’2000; Tagare et al, JMIV’09.

10. a:Original image b,c:Image deformed by two synthetic random transformations d:Deformation retrieved by the proposed method e:Deformation retrieved by the symmetrization method Error in resulting deformations: 0.2% ± 0.2% lower for the proposed method Error in inverse-consistency: 4% ± 2% lower for the proposed method

12. Support provided by: National Institutes of Health Massachusetts Alzheimer’s Disease Research Center BrightFocus Foundation Ellison Medical Foundation Gipuzkoako Foru Aldundia