1 |
A. Coates, A. Y. Ng, and H. Lee, "An analysis of single-layer networks in unsupervised feature learning," Journal of Machine Learning Research, vol. 15, pp. 215-223, 2011.
|
2 |
R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed., Cambridge, UK: Cambridge University Press, 2006.
|
3 |
J. Le Moigne, N. S. Netanyahu, and R. D. Eastman, Image Registration for Remote Sensing, Cambridge, UK: Cambridge University Press, 2011.
|
4 |
J. Le Moigne, "Introduction to remote sensing image registration," in Proc. of 2017 IEEE International Geoscience and Remote Sensing Symposium, pp. 2565-2568, 2017.
|
5 |
S. Agarwal, Y. Furukawa, N. Snavely, I. Simon, B. Curless, S. M. Seitz, and R. Szeliski, "Building Rome in a day," Communications of the ACM, vol. 54, no. 10, 2011.
|
6 |
R. Mur-Artal, J. M. M. Montiel, and J. D. Tardos, "ORB-SLAM: A Versatile and Accurate Monocular SLAM System," IEEE Transactions on Robotics, vol. 31, no. 5, pp. 1147-1163, 2015.
DOI
|
7 |
J. Ma, X. Jiang, A. Fan, J. Jiang, and J. Yan, "Image Matching from Handcrafted to Deep Features: A Survey," International Journal of Computer Vision, 2020.
|
8 |
E. Ferrante and N. Paragios, "Slice-to-volume medical image registration: A survey," Medical Image Analysis, vol. 39, pp. 101-123, 2017.
DOI
|
9 |
Y. Fu, Y. Lei, T. Wang, W. J. Curran, T. Liu, and X. Yang, "Deep Learning in Medical Image Registration: A Review," Physics in Medicine and Biology, vol. 65, no. 20, 2020.
|
10 |
P. Markelj, D. Tomazevic, B. Likar, and F. Pernus, "A review of 3D/2D registration methods for image-guided interventions," Medical Image Analysis, vol. 16, no. 3, pp. 642-661, 2012.
DOI
|
11 |
R. Liao, L. Zhang, Y. Sun, S. Miao, and C. Chefd'Hotel, "A Review of Recent Advances in Registration Techniques Applied to Minimally Invasive Therapy," IEEE Transactions on Multimedia, vol. 15, no. 5, pp. 983-1000, 2013.
DOI
|
12 |
D. G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," International Journal of Computer Vision, vol. 60, pp. 91-110, 2004.
DOI
|
13 |
H. Bay, T. Tuytelaars, and L. Van Gool, "SURF: Speeded Up Robust Features," in Proc. of European Conference on Computer Vision, pp. 404-417, 2006.
|
14 |
E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, "ORB: An efficient alternative to SIFT or SURF," in Proc. of 2011 International Conference on Computer Vision, pp. 2564-2571, 2011.
|
15 |
P. Alcantarilla, J. Nuevo, and A. Bartoli, "Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces," in Proc. of the British machine Vision Conference, pp. 13.1-13.11, 2013.
|
16 |
E. De Castro and C. Morandi, "Registration of Translated and Rotated Images Using Finite Fourier Transforms," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 9, no. 5, pp. 700-703, 1987.
DOI
|
17 |
T. Tuytelaars and K. Mikolajczyk, "Local Invariant Feature Detectors: A Survey," Foundations and Trends® in Computer Graphics and Vision, vol. 3, no. 3, pp. 177-280, 2007.
DOI
|
18 |
K. Mikolajczyk and C. Schmid, "A performance evaluation of local descriptors," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 10, pp. 1615-1630, 2005.
DOI
|
19 |
A. Gruen, "Development and Status of Image Matching in Photogrammetry," in Proc. of Ian Dowman Retirement Symposium, vol. 27, no. 137, pp. 36-57, 2012.
|
20 |
B. S. Reddy and B. N. Chatterji, "An FFT-based technique for translation, rotation, and scaleinvariant image registration," IEEE Transactions on Image Processing, vol. 5, no. 8, pp. 1266-1271, 1996.
DOI
|
21 |
X. Tong, K. Luan, U. Stilla, Z. Ye, Y. Xu, S. Gao, H. Xie, Q. Du, S. Liu, X. Xu, and S. Liu, "Image Registration With Fourier-Based Image Correlation: A Comprehensive Review of Developments and Applications," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 10, pp. 4062-4081, 2019.
DOI
|
22 |
J. P. Lewis, "Fast Template Matching," Vision Interface, Quebec City, QC, Canada, pp. 120-123, 1995.
|
23 |
L. Jing and Y. Tian, "Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, p. 1, 2020.
|
24 |
A. Krizhevsky, "Learning multiple layers of features from tiny images," Univ. of Toronto, Toronto, ON, Canada, 2009.
|
25 |
D. Kingma and J. Ba, "Adam: A Method for Stochastic Optimization," in Proc. of International Conference on Learning Representations, 2014.
|
26 |
B. Zitova and J. Flusser, "Image registration methods: a survey," Image and Vision Computing, vol. 21, no. 11, pp. 977-1000, 2003.
DOI
|
27 |
D. A. Forsyth and J. Ponce, Computer Vision: A Modern Approach. Englewood Cliffs, NJ, USA: Prentice Hall, 2003.
|
28 |
S. S. M. Salehi, S. Khan, D. Erdogmus, and A. Gholipour, "Real-Time Deep Pose Estimation with Geodesic Loss for Image-to-Template Rigid Registration," IEEE Transactions on Medical Imaging, vol. 38, no. 2, pp. 470-481, Feb. 2019.
DOI
|
29 |
S. Hochreiter and J. Schmidhuber, "Long short-term memory," Neural Computation, vol. 9, no. 8, pp. 1735-1780, 1997.
DOI
|
30 |
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, A. Desmaison, A. Kopf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, and S. Chintala, "PyTorch: An imperative style, high-performance deep learning library," Advances in Neural Information Processing Systems, 2019.
|
31 |
S. Xie, R. Girshick, P. Dollar, Z. Tu, and K. He, "Aggregated Residual Transformations for Deep Neural Networks," in Proc. of 2017 IEEE Conference on Computer Vision and Pattern Recognition(CVPR), pp. 5987-5995, 2017.
|
32 |
J. Deng, W. Dong, R. Socher, L. Li, K. Li, and L. Fei-Fei, "ImageNet: A large-scale hierarchical image database," in Proc. of 2017 IEEE Conference on Computer Vision and Pattern Recognition(CVPR), pp. 248-255, 2019.
|
33 |
F. L. Bookstein, "Principal warps: thin-plate splines and the decomposition of deformations," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 6, pp. 567-585, 1989.
DOI
|
34 |
V. Villena-Martinez, S. Oprea, M. Saval-Calvo, J. Azorin-Lopez, A. Fuster-Guillo, and R. B. Fisher, "When Deep Learning Meets Data Alignment: A Review on Deep Registration Networks (DRNs)," Applied Sciences, vol. 10, no. 21, p. 7524, 2020.
DOI
|
35 |
T. Nguyen, S. W. Chen, S. S. Shivakumar, C. J. Taylor, and V. Kumar, "Unsupervised Deep Homography: A Fast and Robust Homography Estimation Model," IEEE Robotics and Automation Letters, vol. 3, no. 3, pp. 2346-2353, 2018.
DOI
|
36 |
I. Rocco, R. Arandjelovic, and J. Sivic, "Convolutional Neural Network Architecture for Geometric Matching," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 11, pp. 2553-2567, 2019.
DOI
|
37 |
K. Simonyan and A. Zisserman, "Very deep convolutional networks for large-scale image recognition," arXiv preprint arXiv:1409.1556, 2015.
|
38 |
Z. Chen, Z. Xu, Q. Gui, X. Yang, Q. Cheng, W. Hou, and M. Ding, "Self-learning based medical image representation for rigid real-time and multimodal slice-to-volume registration," Information Sciences, vol. 541, pp. 502-515, 2020.
DOI
|
39 |
S. Miao, Z. J. Wang and R. Liao, "A CNN Regression Approach for Real-Time 2D/3D Registration," IEEE Transactions on Medical Imaging, vol. 35, no. 5, pp. 1352-1363, May 2016.
DOI
|
40 |
J. M. SloanK, A. Goatman, and J. P. Siebert, "Learning Rigid Image Registration - Utilizing Convolutional Neural Networks for Medical Image Registration," in Proc. of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, vol. 2, pp. 89-99, 2018.
|
41 |
M. A. Fischler and R. C. Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography," Communications of the ACM, vol. 24, no. 6, 1981.
|
42 |
T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, and A. Y. Wu, "An efficient k-means clustering algorithm: analysis and implementation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 881-892, July 2002.
DOI
|