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Traditional deformable registration techniques achieve impressive results and offer a rigorous theoretical treatment, but are computationally intensive since they solve an optimization problem for each image pair.
Multiresolution elastic matching
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Nonrigid registration using free-form deformation: Application to breast mr images
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Hammer: Hierarchical attribute matching mechanism for elastic registration
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Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain
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Dense image registration through mrfs and efficient linear programming
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Evaluation of 14 nonlinear deformation algorithms applied to human brain mri registration
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Patch-based discrete registration of clinical brain images
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End-to-end unsupervised deformable image registration with a convolutional neural network
Bob D de Vos, Floris F Berendsen, Max A Viergever, Marius Staring, and Ivana Išgum · 2017
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Non-rigid image registration using fully convolutional networks with deep self-supervision
H. Li and Y. Fan · 2017
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Alexander Dagley, Molly LaPoint, Willem Huijbers, Trey Hedden, Donald G McLaren, Jasmeer P Chatwal, Kathryn V Papp, Rebecca E Amariglio, Deborah Blacker, Dorene M Rentz, et al · 2015
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Avram J Holmes, Marisa O Hollinshead, Timothy M O’Keefe, Victor I Petrov, Gabriele R Fariello, Lawrence L Wald, Bruce Fischl, Bruce R Rosen, Ross W Mair, Joshua L Roffman, et al · 2015
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Spatial transformer networks
Max Jaderberg, Karen Simonyan, and Andrew Zisserman · 2015
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Nonrigid image registration using multi-scale 3d convolutional neural networks
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Quicksilver: Fast predictive image registration–a deep learning approach
Xiao Yang, Roland Kwitt, Martin Styner, and Marc Niethammer · 2017
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Frequency diffeomorphisms for efficient image registration
Miaomiao. Zhang, Ruizhi. Liao, Adrian V Dalca, Esra A Turk, Jie Luo, P Ellen Grant, and Polina Golland · 2017
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An unsupervised learning model for deformable medical image registration
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