Non-iterative Coarse-to-Fine Registration Based on Single-Pass Deep Cumulative Learning
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Publisher
Springer Nature Switzerland
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https://link.springer.com/content/pdf/10.1007/978-3-031-16446-0_9
Reference25 articles.
1. Haskins, G., Kruger, U., Yan, P.: Deep learning in medical image registration: a survey. Mach. Vis. Appl. 31(1–2), 1–18 (2020). https://doi.org/10.1007/s00138-020-01060-x
2. Sotiras, A., Davatzikos, C., Paragios, N.: Deformable medical image registration: a survey. IEEE Trans. Med. Imaging. 32(7), 1153–1190 (2013)
3. Xiao, H., et al.: A review of deep learning-based three-dimensional medical image registration methods. Quant. Imaging Med. Surg. 11(12), 4895–4916 (2021)
4. Balakrishnan, G., Zhao, A., Sabuncu, M.R., Guttag, J., Dalca, A.V.: Voxelmorph: a learning framework for deformable medical image registration. IEEE Trans. Med. Imaging 38(8), 1788–1800 (2019)
5. Dalca, A.V., Balakrishnan, G., Guttag, J., Sabuncu, M.R.: Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces. Med. Image Anal. 57, 226–236 (2019)
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