The DOI matches its Crossref record; 19 of the 20 references it cites were found in a registry or an index.
Fast Predictive Image Registration
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“At first, Yang et al. (73) proposed to register brain MRI images using a U-Net-like structure in one step.”
From A review of deep learning-based deformable medical image registration (2022) · cites this paper as [73]
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Citations
Cites
Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148
(2014) · Cited by 33,419
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
He, K., Zhang, X., Ren, S., & Sun, J. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.123 · Cited by 19,741
Flownet: Learning optical flow with convolutional networks
Dosovitskiy, A., Fischer, P., Ilg, E., Hausser, P., Hazirbas, C., Golkov, V., Smagt, P. V. D., Cremers, D., & Brox, T. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.316 · Cited by 4,313
Marcus, D. S., Wang, T. H., Parker, J., Csernansky, J. G., Morris, J. C., & Buckner, R. L. (2007) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2007.19.9.1498 · Cited by 2,163
Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms
Beg, M. F., Miller, M. I., Trouvé, A., & Laurent Younes, B. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000043755.93987.aa · Cited by 1,764
DeepFlow: Large Displacement Optical Flow with Deep Matching
Weinzaepfel, P., Revaud, J., Harchaoui, Z., & Schmid, C. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.175 · Cited by 1,057
Numerical Methods for Image Registration
Jan Modersitzki, C. (2003) · doi:10.1093/acprof:oso/9780198528418.001.0001 · Cited by 926
Unbiased diffeomorphic atlas construction for computational anatomy
Joshi, S. C., Davis, B. C., Jomier, M., & Gerig, G. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.068 · Cited by 881
FlowNet: Learning Optical Flow with Convolutional NetworksPreprint
Fischer, P., Dosovitskiy, A., Ilg, E., Haeusser, P., Hazırbaş, C., Golkov, V., van der Smagt, P., Cremers, D., & Brox, T. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1504.06852 · Cited by 814
Cited by
Sorted by citations
A survey on deep learning in medical image analysis
Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.07.005 · Cited by 15,332
TransMorph: Transformer for unsupervised medical image registration
Chen, J., Frey, E. C., He, Y., Segars, W. P., Li, Y., & Du, Y. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102615 · Cited by 883
Deep learning in medical image registration: a survey
Haskins, G., Kruger, U., & Yan, P. (2020) · Machine Vision and Applications · doi:10.1007/s00138-020-01060-x · Cited by 704
A review on deep learning in medical image analysis
Suganyadevi, S., Seethalakshmi, V., & Balasamy, K. (2021) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-021-00218-1 · Cited by 717
Quicksilver: Fast predictive image registration – A deep learning approach
Yang, X., Kwitt, R., Styner, M., & Niethammer, M. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.008 · Cited by 630
“The registration method described here, which we name Quicksilver, is an extension of preliminary ideas we presented in a recent workshop paper [21].”
MethodSelf-citation
Metadata
- Authors
- Yang, X., Kwitt, R., & Niethammer, M.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- University of Salzburg (AT)
- Corresponding author
- Yang, Xiao
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 48-57
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2482922118
- Cited by
- 127
- References
- 20
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 10 · 2023: 17 · 2022: 14 · 2021: 18 · 2020: 14 · 2019: 23 · 2018: 8 · 2017: 17
- FWCI
- 5.55
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- image registration, deformation prediction, LDDMM, diffeomorphic registration, Bayesian neural networks, uncertainty estimation, dropout, brain MRI registration, OASIS dataset
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