title: Asymmetric image-template registration.
abstract: A natural requirement in pairwise image registration is that the resulting deformation is independent of the order of the images. This constraint is typically achieved via a symmetric cost function and has been shown to reduce the effects of local optima. Consequently, symmetric registration has been successfully applied to pairwise image registration as well as the spatial alignment of individual images with a template. However, recent work has shown that the relationship between an image and a template is fundamentally asymmetric. In this paper, we develop a method that reconciles the practical advantages of symmetric registration with the asymmetric nature of image-template registration by adding a simple correction factor to the symmetric cost function. We instantiate our model within a log-domain diffeomorphic registration framework. Our experiments show exploiting the asymmetry in image-template registration improves alignment in the image coordinates.
authors.affiliation: Computer Science and Artificial Intelligence Lab, MIT, Harvard Medical School, USA.
authors.forename: Mert R
authors.initials: MR
authors.lastname: Sabuncu
authors.forename: B T Thomas
authors.initials: BT
authors.lastname: Yeo
authors.forename: Koen
authors.initials: K
authors.lastname: Van Leemput
authors.forename: Tom
authors.initials: T
authors.lastname: Vercauteren
authors.forename: Polina
authors.initials: P
authors.lastname: Golland
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique