Deep Learning Based Inter-modality Image Registration Supervised by Intra-modality Similarity
Open accessAbstract
Non-rigid inter-modality registration can facilitate accurate information fusion from different modalities, but it is challenging due to the very different image appearances across modalities. In this paper, we propose to train a non-rigid inter-modality image registration network, which can directly predict the transformation field from the input multimodal images, such as CT and MR images. In particular, the training of our inter-modality registration network is supervised by intra-modality similarity metric based on the available paired data, which is derived from a pre-aligned CT and MR dataset. Specifically, in the training stage, to register the input CT and MR images, their similarity is evaluated on the warped MR image and the MR image that is paired with the input CT. So that, the intra-modality similarity metric can be directly applied to measure whether the input CT and MR images are well registered. Moreover, we use the idea of dual-modality fashion, in which we measure the similarity on both CT modality and MR modality. In this way, the complementary anatomies in both modalities can be jointly considered to more accurately train the inter-modality registration network. In the testing stage, the trained inter-modality registration network can be directly applied to register the new multimodal images without any paired data. Experimental results have shown that, the proposed method can achieve promising accuracy and efficiency for the challenging non-rigid inter-modality registration task and also outperforms the state-of-the-art approaches.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In medical imaging applications with human tissues, registration of slices must be performed in an elastic form.
“In medical imaging applications with human tissues, registration of slices must be performed in an elastic form [195].”
From AI in Medical Imaging Informatics: Current Challenges and Future Directions (2020) · cites this paper as [195]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404 · see citing works
Advances in neural information processing systems 7
Cios, K. J., & Shields, M. E. (1997) · Neurocomputing · doi:10.1016/s0925-2312(97)90018-7 · Cited by 22,089 · see citing works
A global optimisation method for robust affine registration of brain images
Jenkinson, M., & Smith, S. M. (2001) · Medical Image Analysis · doi:10.1016/s1361-8415(01)00036-6 · Cited by 6,806 · see citing works
Avants, B., Epstein, C. L., Grossman, M., & Gee, J. C. (2007) · Medical Image Analysis · doi:10.1016/j.media.2007.06.004 · Cited by 5,618 · see citing works
Mutual-information-based registration of medical images: a survey
Pluim, J. P. W., Maintz, J. B. A., & Viergever, M. A. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.815867 · Cited by 2,882 · see citing works
End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network
de Vos, B. D., Berendsen, F. F., Viergever, M. A., Staring, M., & Išgum, I. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-67558-9_24 · Cited by 456 · see citing works
Non-parametric Diffeomorphic Image Registration with the Demons Algorithm
Vercauteren, T. K., Pennec, X., Aymeric Perchant, B., & Ayache, N. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-75759-7_39 · Cited by 380 · see citing works
Deformable Image Registration Using a Cue-Aware Deep Regression Network
Cao, X., Yang, J., Zhang, J., Wang, Q., Yap, P., & Shen, D. G. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2822826 · Cited by 123 · see citing works
Self-citationRegion-Adaptive Deformable Registration of CT/MRI Pelvic Images via Learning-Based Image Synthesis
Cao, X., Yang, J., Gao, Y., Wang, Q., & Shen, D. G. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2820424 · Cited by 51 · see citing works
Self-citation
Flagged first, then by citations
1 of the 10 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
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 826 · see citing works
AI in Medical Imaging Informatics: Current Challenges and Future Directions
Panayides, A. S., Amini, A., Filipovic, N. D., Sharma, A., Tsaftaris, S. A., Young, A., Foran, D., Do, N., Golemati, S., Kurc, T., et al. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2991043 · Cited by 713 · see citing works
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 · see citing works
Deep learning in medical image registration: a review
Fu, Y., Lei, Y., Wang, T., Curran, W. J., Liu, T., & Yang, X. (2020) · Physics in Medicine & Biology · doi:10.1088/1361-6560/ab843e · Cited by 661 · see citing works
A review of multimodal image matching: Methods and applications
Jiang, X., Ma, J.-Y., Xiao, G.-B., Shao, Z.-F., & Guo, X.-J. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.02.012 · Cited by 476 · see citing works
CycleMorph: Cycle consistent unsupervised deformable image registration
Kim, B., Kim, D. H., Park, S. H., Kim, J., Lee, J., & Ye, J. C. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102036 · Cited by 346 · see citing works
Wang, D., Liu, J., Fan, X., & Liu, R. (2022) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2022/487 · Cited by 342 · see citing works
Infrared and Visible Image Fusion: From Data Compatibility to Task Adaption
Liu, J., Wu, G., Liu, Z., Wang, D., Jiang, Z., Ma, L., Zhong, W., Fan, X., & Liu, R. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3521416 · Cited by 238 · see citing works
Multi-Modal Remote Sensing Image Matching Considering Co-Occurrence Filter
Yao, Y., Zhang, Y., Wan, Y., Liu, X., Yan, X., & Li, J. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3157450 · Cited by 185 · see citing works
Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation
Arar, M., Ginger, Y., Danon, D., Bermano, A. H., & Cohen‐Or, D. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01342 · Cited by 182 · see citing works
Medical image registration using deep neural networks: A comprehensive review
Boveiri, H. R., Khayami, R., Javidan, R., & Mehdizadeh, A. (2020) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2020.106767 · Cited by 179 · see citing works
Adversarial learning for mono- or multi-modal registration
Fan, J., Cao, X., Wang, Q., Yap, P., & Shen, D. G. (2019) · Medical Image Analysis · doi:10.1016/j.media.2019.101545 · Cited by 169 · see citing works
Self-citationMahmood, T., Rehman, A. U., Saba, T., Nadeem, L., & Bahaj, S. A. (2023) · IEEE Access · doi:10.1109/access.2023.3313977 · Cited by 155 · see citing works
Deep Learning in Medical Image Registration
Chen, X., Diaz-Pinto, A., Ravikumar, N., & Frangi, A. (2020) · Progress in Biomedical Engineering · doi:10.1088/2516-1091/abd37c · Cited by 106 · see citing works
DiffuseMorph: Unsupervised Deformable Image Registration Using Diffusion Model
Kim, B., Han, I., & Ye, J. C. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19821-2_20 · Cited by 102 · see citing works
Adversarial Image Registration with Application for MR and TRUS Image Fusion
Yan, P., Xu, S., Rastinehad, A. R., & Wood, B. J. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-00919-9_23 · Cited by 100 · see citing works
Nenoff, L., Amstutz, F., Murr, M., Archibald‐Heeren, B. R., Fusella, M., Hussein, M., Lechner, W., Zhang, Y., Sharp, G., & Osorio, E. M. V. (2023) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ad0d8a · Cited by 99 · see citing works
A review of deep learning-based deformable medical image registration
Zou, J., Gao, B., Song, Y., & Qin, J. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.1047215 · Cited by 91 · see citing works
Improving Misaligned Multi-Modality Image Fusion With One-Stage Progressive Dense Registration
Wang, D., Liu, J., Ma, L., Liu, R., & Fan, X. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3412743 · Cited by 82 · see citing works
Huang, W., Yang, H., Liu, X., Li, C., Zhang, I., Wang, R., Zheng, H., & Wang, S. (2021) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2021.3059282 · Cited by 81 · see citing works
A review of deep learning-based three-dimensional medical image registration methods
Xiao, H., Teng, X., Liu, C., Li, T., Ren, G., Yang, R., Shen, D., & Cai, J. (2021) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims-21-175 · Cited by 77 · see citing works
Self-citationArtificial Intelligence in Radiation Therapy
Fu, Y., Zhang, H., Morris, E. D., Glide‐Hurst, C. K., Pai, S., Traverso, A., Wee, L., Hadžić, I., Lønne, P.-I., Shen, C., et al. (2021) · IEEE Transactions on Radiation and Plasma Medical Sciences · doi:10.1109/trpms.2021.3107454 · Cited by 72 · see citing works
Adversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration
Xu, Z., Luo, J., Yan, J., Pulya, R., Li, X., Wells, W. M., & Jayender, J. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59716-0_22 · Cited by 69 · see citing works
Han, R., Jones, C. K., Lee, J., Wu, P., Vagdargi, P., Uneri, A., Helm, P. A., Luciano, M., Anderson, W. S., & Siewerdsen, J. H. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102292 · Cited by 66 · see citing works
Multimodal imaging and machine learning to enhance microscope images of shale
Anderson, T. I., Vega, B., & Kovscek, A. R. (2020) · Computers & Geosciences · doi:10.1016/j.cageo.2020.104593 · Cited by 63 · see citing works
Machine learning for radiomics-based multimodality and multiparametric modeling
Wei, L., Osman, S. O. S., Hatt, M., & Naqa, I. E. (2019) · The Quarterly Journal of Nuclear Medicine and Molecular Imaging · doi:10.23736/s1824-4785.19.03213-8 · Cited by 61 · see citing works
AMNet: Adaptive multi-level network for deformable registration of 3D brain MR images
Che, T., Wang, X., Zhao, K., Zhao, Y., Zeng, D., Li, Q., Zheng, Y., Yang, N., Wang, J., & Li, S. (2023) · Medical Image Analysis · doi:10.1016/j.media.2023.102740 · Cited by 52 · see citing works
Recent Applications of Artificial Intelligence in Radiotherapy: Where We Are and Beyond
Santoro, M., Strolin, S., Paolani, G., Gala, G. D., Bartoloni, A., Giacometti, C., Ammendolia, I., MORGANTI, A. G., & Strigari, L. (2022) · Applied Sciences · doi:10.3390/app12073223 · Cited by 51 · see citing works
Tadavarthi, Y., Makeeva, V., Wagstaff, W., Zhan, H. T., Podlasek, A., Bhatia, N. K., Heilbrun, M. E., Krupinski, E. A., Safdar, N. M., Banerjee, I., et al. (2022) · Radiology Artificial Intelligence · doi:10.1148/ryai.210114 · Cited by 50 · see citing works
Artificial intelligence in radiotherapy: a technological review
Sheng, K. (2020) · Frontiers of Medicine · doi:10.1007/s11684-020-0761-1 · Cited by 44 · see citing works
Chen, X., Zhou, H.-Y., Liu, F., Guo, J., Wang, L., & Yu, Y. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102506 · Cited by 41 · see citing works
Self-citationAn application independent review of multimodal 3D registration methods
Saiti, E., & Theoharis, T. (2020) · Computers & Graphics · doi:10.1016/j.cag.2020.07.012 · Cited by 40 · see citing works
Khor, H. G., Ning, G., Sun, Y., Xu, L., Zhang, X., & Liao, H. (2023) · Medical Image Analysis · doi:10.1016/j.media.2023.102811 · Cited by 38 · see citing works
Application of Image Fusion in Diagnosis and Treatment of Liver Cancer
Li, C., & Zhu, A. X. (2020) · Applied Sciences · doi:10.3390/app10031171 · Cited by 38 · see citing works
Liu, Y., Wang, W., Li, Y., Lai, H., Huang, S., & Yang, X. N. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2023.3270199 · Cited by 37 · see citing works
Elmahdy, M. S., Beljaards, L., Yousefi, S., Sokooti, H., Verbeek, F. J., van der Heide, U. A., & Staring, M. (2021) · IEEE Access · doi:10.1109/access.2021.3091011 · Cited by 34 · see citing works
Artificial general intelligence for radiation oncology
Liu, C., Liu, Z., Holmes, J., Zhang, L., Zhang, L., Ding, Y., Shu, P., Wu, Z., Dai, H., Li, Y., et al. (2023) · Meta-Radiology · doi:10.1016/j.metrad.2023.100045 · Cited by 34 · see citing works
Self-citationCoCycleReg: Collaborative cycle-consistency method for multi-modal medical image registration
Lian, C., Li, X., Kong, L., Wang, J., Zhang, W., Huang, X., & Wang, L. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.05.113 · Cited by 33 · see citing works
Self-citationMR to ultrasound image registration with segmentation‐based learning for HDR prostate brachytherapy
Chen, Y., Xing, L., Yu, L., Liu, W., Fahimian, B., Niedermayr, T. R., Bagshaw, H. P., Buyyounouski, M. K., & Han, B. (2021) · Medical Physics · doi:10.1002/mp.14901 · Cited by 32 · see citing works
NBR-Net: A Nonrigid Bidirectional Registration Network for Multitemporal Remote Sensing Images
Xu, Y., Jun, L., Du, C., & Chen, H. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3162094 · Cited by 32 · see citing works
Image Registration in Medical Robotics and Intelligent Systems: Fundamentals and Applications
Liu, J., Singh, G., Alaref, S. J., Lee, B., Oleru, O. O., Min, J. K., Dunham, S. N., Sabuncu, M. R., & Mosadegh, B. (2019) · Advanced Intelligent Systems · doi:10.1002/aisy.201900048 · Cited by 29 · see citing works
Deep learning for improving PET/CT attenuation correction by elastic registration of anatomical data
Schaefferkoetter, J. D., Shah, V. P., Hayden, C., Prior, J. O., & Zuehlsdorff, S. (2023) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-023-06181-9 · Cited by 28 · see citing works
Deep Group-Wise Registration for Multi-Spectral Images From Fundus Images
Che, T., Zheng, Y., Cong, J., Jiang, Y., Niu, Y., Jiao, W., Zhao, B., & Ding, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2901580 · Cited by 27 · see citing works
Modal-invariant progressive representation for multimodal image registration
Ding, J., Zhao, Y., Pei, L., Shan, Y., Du, Y., & Li, W. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102903 · Cited by 23 · see citing works
MultiGradICON: A Foundation Model for Multimodal Medical Image Registration
Demir, B., Tian, L., Greer, H., Kwitt, R., Vialard, F., Estépar, R. S. J., Sylvain Bouix, A., Rushmore, J., Ebrahim, E., & Niethammer, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73480-9_1 · Cited by 22 · see citing works
Transfer Learning for Nonrigid 2D/3D Cardiovascular Images Registration
Guan, S., Wang, T., Sun, K., & Cai, M. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.3045977 · Cited by 22 · see citing works
A review on 3D deformable image registration and its application in dose warping
Xiao, H., Ren, G., & Cai, J. (2020) · Radiation Medicine and Protection · doi:10.1016/j.radmp.2020.11.002 · Cited by 20 · see citing works
A variational Bayesian method for similarity learning in non-rigid image registration
Grzech, D., Azampour, M. F., Glocker, B., Schnabel, J. A., Navab, N., Kainz, B., & Folgoc, L. L. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00022 · Cited by 19 · see citing works
A Transformer-Based Network for Deformable Medical Image Registration
Wang, Y., Qian, W., Li, M., & Zhang, X. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20497-5_41 · Cited by 19 · see citing works
Gu, D., Shi, F., Hua, R., Wei, Y., Li, Y., Zhu, J., Zhang, W., Zhang, H., Yang, Q., Huang, P., et al. (2022) · Human Brain Mapping · doi:10.1002/hbm.26126 · Cited by 17 · see citing works
Self-citationAU-Net: Adaptive Unified Network for Joint Multi-Modal Image Registration and Fusion
Lu, M., Jiang, M., Tao, X., & Kong, J. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3586507 · Cited by 15 · see citing works
Multitask Weakly Supervised Generative Network for MR-US Registration
Azampour, M. F., Mach, K., Fatemizadeh, E., Demiray, B., Westenfelder, K. M., Steiger, K., Eiber, M., Wendler, T., Kainz, B., & Navab, N. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3400899 · Cited by 15 · see citing works
Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
Kim, J., Yoon, H., Park, G., Kim, K., & Yang, E. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01079 · Cited by 15 · see citing works
DGR-Net: Deep Groupwise Registration of Multispectral Images
Che, T., Zheng, Y., Sui, X., Jiang, Y., Cong, J., Jiao, W., & Zhao, B. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-20351-1_55 · Cited by 14 · see citing works
Yu, X., He, L. L., Wang, Y., Dong, Y., Song, Y., Yuan, Z., Yan, Z., & Wang, W. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1235461 · Cited by 13 · see citing works
Zhou, Z., Wang, S., Hu, J., Liu, A., Qian, X., Chen, G., Zheng, J., Chen, G., Ji, J., & Dai, Y. (2023) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2023.102260 · Cited by 12 · see citing works
2D-to-3D image translation of complex nanoporous volumes using generative networks
Anderson, T. I., Vega, B., Mckinzie, J., Aryana, S. A., & Kovscek, A. R. (2021) · Scientific Reports · doi:10.1038/s41598-021-00080-5 · Cited by 12 · see citing works
Yang, W., Yao, Y., Zhang, Y., & Wan, Y. (2023) · The Photogrammetric Record · doi:10.1111/phor.12464 · Cited by 12 · see citing works
Wang, D., Jiao, X., Liu, J., & Fan, X. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3535291 · Cited by 11 · see citing works
Wang, C., Yang, G., & Papanastasiou, G. (2022) · Sensors · doi:10.3390/s22062125 · Cited by 11 · see citing works
General cross-modality registration framework for visible and infrared UAV target image registration
Luo, Y., Cha, H., Zuo, L., Cheng, P., & Zhao, Q. (2023) · Scientific Reports · doi:10.1038/s41598-023-39863-3 · Cited by 10 · see citing works
Sadeghi, M. H., Sina, S., Alavi, M., Giammarile, F., & Yeong, C. H. (2024) · Physical and Engineering Sciences in Medicine · doi:10.1007/s13246-024-01485-y · Cited by 10 · see citing works
Deep multispectral image registration network
Sui, X., Zheng, Y., Jiang, Y., Jiao, W., & Ding, Y. (2020) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2020.101815 · Cited by 10 · see citing works
UTR: A UNet-like transformer for efficient unsupervised medical image registration
Qiu, W., Xiong, L., Li, N., Wang, Y., & Zhang, Y. (2024) · Image and Vision Computing · doi:10.1016/j.imavis.2024.105209 · Cited by 10 · see citing works
A Novel Computer-Assisted System for Long Bone Fracture Reduction With a Hexapod External Fixator
Liu, C., Liu, S., Wang, Y., Fu, X., & Sun, T. (2024) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2024.3494756 · Cited by 9 · see citing works
Firefly-Based Approaches of Image Recognition
COCIANU, C. L., Stan, A., & Avramescu, M. (2020) · Symmetry · doi:10.3390/sym12060881 · Cited by 9 · see citing works
Unsupervised Multi-modal Medical Image Registration via Invertible Translation
Guo, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72751-1_2 · Cited by 8 · see citing works
W-NetPan: Double-U network for inter-sensor self-supervised pan-sharpening
Fernández-Beltrán, R., Fernandez, R., Kang, J. S., & Pla, F. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.02.002 · Cited by 7 · see citing works
Deep learning-based medical image registration
Cao, X., Xue, P., Fan, J., Liu, D., Sun, K., Xue, Z., & Shen, D. G. (2024) · Elsevier eBooks · doi:10.1016/b978-0-32-385124-4.00023-4 · Cited by 7 · see citing works
Self-citationTwo-Stage Unsupervised Learning Method for Affine and Deformable Medical Image Registration
Gu, D., Liu, G., Tian, J., & Zhan, Q. (2019) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2019.8803794 · Cited by 7 · see citing works
Unimodal Cyclic Regularization For Training Multimodal Image Registration Networks
Xu, Z., Yan, J., Luo, J., Wells, W. M., Li, X., & Jayender, J. (2021) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi48211.2021.9433926 · Cited by 7 · see citing works
Mu, K., Wang, W., Liu, H., Liang, L., & Zhang, S. (2025) · Remote Sensing · doi:10.3390/rs17061071 · Cited by 6 · see citing works
Chang, Y., & Li, Z. (2025) · Medical Image Analysis · doi:10.1016/j.media.2025.103713 · Cited by 6 · see citing works
Li, L., Li, L., Zhang, Y., Bao, F., Yao, X., & Zhang, C. (2025) · Applied Intelligence · doi:10.1007/s10489-025-06232-8 · Cited by 6 · see citing works
Tiwari, A. S., Chaudhari, M., & Rai, A. (2019) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac47947.2019.9032566 · Cited by 6 · see citing works
An Unsupervised Deep Learning Method for Diffeomorphic Mono-and Multi-modal Image Registration
Theljani, A., & Chen, K. (2020) · Communications in computer and information science · doi:10.1007/978-3-030-39343-4_27 · Cited by 6 · see citing works
Multi-temporal Registration of Environmental Imagery Using Affine Invariant Convolutional Features
Khan, A. A., Ulhaq, A., & Robinson, R. W. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-34879-3_21 · Cited by 5 · see citing works
DPCN++: Differentiable Phase Correlation Network for Versatile Pose Registration
Chen, Z., Liao, Y., Du, H., Zhang, H., Xu, X., Lu, H., Xiong, R., & Wang, Y. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3317501 · Cited by 5 · see citing works
An Unsupervised Approach for 3D Medical Image Registration
Ma, Y., Zhang, J., Niu, D., Hassan, M. U., & Zhao, X. (2019) · International Conference on Information Technology: IoT and Smart City (ICIT) · doi:10.1145/3377170.3377273 · Cited by 5 · see citing works
Artificial Intelligence in Radiation Therapy
Sumida, I. (2022) · Institute of Physics eBooks · doi:10.1088/978-0-7503-3339-9 · Cited by 5 · see citing works
End-to-End Multi-Slice-to-Volume Concurrent Registration and Multimodal Generation
Leroy, A., Lerousseau, M., Henry, T., Cafaro, A., Nikos Paragios, A., Grégoire, V., & Deutsch, É. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16446-0_15 · Cited by 5 · see citing works
Lajili, M., Belhachmi, Z., Moakher, M., & Theljani, A. (2024) · Applied Intelligence · doi:10.1007/s10489-024-05585-w · Cited by 4 · see citing works
Enhancing 3D medical image registration with cross attention, residual skips, and cascade attention
Anwar, M., He, Z., & Cao, W. (2024) · Intelligent Data Analysis · doi:10.3233/ida-230692 · Cited by 4 · see citing works
Segmentation outperforms registration in quantitative analysis of brain iron
He, J., Fu, B., Wang, B., Xiong, Z., Peng, Y., & Wang, R. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.107446 · Cited by 4 · see citing works
Wang, Y., Zhang, Y., Ma, C., Wang, R., Guo, Z., Shen, Y., Wang, M., & Meng, H. (2023) · International Journal of Neural Systems · doi:10.1142/s0129065724500011 · Cited by 4 · see citing works
CrossModalNet: exploiting quality preoperative images for multimodal image registration
Sun, J., Liu, C., Li, C., Lu, Z., He, M., Gao, L., Lin, T., Sui, J., Xie, K., & Ni, X. (2021) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ac195e · Cited by 4 · see citing works
FAMAFuse: Functional-Anatomical Multiscale Attention for Multimodal Image Fusion
Kamara, A. A., He, S., & Fofanah, A. J. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3626562 · Cited by 3 · see citing works
Zhang, X., Gosnell, J. M., Nainamalai, V., Page, S., Huang, S., Haw, M. P., Peng, B., Vettukattil, J. J., & Jiang, J. (2023) · Diagnostics · doi:10.3390/diagnostics13182981 · Cited by 3 · see citing works
Wu, C., & Li, Z. (2025) · The Visual Computer · doi:10.1007/s00371-025-04183-2 · Cited by 3 · see citing works
Unpaired Cross-Modal Interaction Learning for COVID-19 Segmentation on Limited CT Images
Guan, Q., Xie, Y., Yang, B., Zhang, J., Liao, Z., Wu, Q., & Xia, Y. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-43898-1_58 · Cited by 3 · see citing works
Intraoperative CT Augmentation for Needle-Based Liver Interventions
Hadramy, S. E., Verde, J. M., Padoy, N., & Cotin, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-43996-4_28 · Cited by 3 · see citing works
Ji, Y., Zhu, Z., & Wei, Y. (2022) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi52829.2022.9761527 · Cited by 3 · see citing works
Communal Domain Learning for Registration in Drifted Image Spaces
Mansoor, A., & Linguraru, M. G. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-32692-0_55 · Cited by 3 · see citing works
Modern Approaches for Thoracic Image Registration and Respiratory Motion Management in Oncology
Jank, E., Liu, E. Y., Delery, W., Boyle, P., Miller, C. R., Andosca, R., Naumann, L., Upadhyay, R., Kadambi, A., Low, D. A., et al. (2025) · Radiology Imaging Cancer · doi:10.1148/rycan.250023 · Cited by 2 · see citing works
Pan, T., Thomas, M. A., Lü, Y., & Luo, D. (2025) · EJNMMI Physics · doi:10.1186/s40658-025-00797-6 · Cited by 2 · see citing works
Jiang, M., Gao, S., Zhang, X., Wang, X., Hu, Q., & Wang, W. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112684 · Cited by 2 · see citing works
Self-supervised Probe Pose Regression via Optimized Ultrasound Representations for US-CT Fusion
Azampour, M. F., Velikova, Y., Fatemizadeh, E., Dakua, S. P., & Navab, N. (2024) · Lecture notes in electrical engineering · doi:10.1007/978-981-97-1335-6_11 · Cited by 2 · see citing works
Huang, Q., Ren, L., Quan, T., Yang, M., Yuan, H., & Cao, K. (2024) · Journal of Innovative Optical Health Sciences · doi:10.1142/s1793545824500226 · Cited by 2 · see citing works
Momoh, H., Ibrahim, H. A., Abdulmalik, M. O., & Bello, A. I. (2024) · Journal of applied science and environmental management · doi:10.4314/jasem.v28i4.8 · Cited by 2 · see citing works
New Attempts in Solving Image Recognition Tasks
COCIANU, C. L., Stan, A., & Avramescu, M. (2019) · Communications in computer and information science · doi:10.1007/978-3-030-30275-7_36 · Cited by 2 · see citing works
- Authors
- Cao, X., Yang, J., Wang, L., Xue, Z., Wang, Q., & Shen, D.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Northwestern Polytechnical University (CN)
- United Imaging Intelligence (China) (CN)
- Shanghai Jiao Tong University (CN)
- Corresponding author
- Shen, Dinggang
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Volume
- 11046
- Pages
- 55-63
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- PMC
- PMC6516490
- OpenAlex
- W2798741430
- Cited by
- 123
- References
- 10
- Citations by year
- 2026: 7 · 2025: 16 · 2024: 19 · 2023: 21 · 2022: 18 · 2021: 14 · 2020: 16 · 2019: 11 · 2018: 1
- FWCI
- 3.16
- Type
- conference paper
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Lecture notes in computer science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Institute on Aging (RF1AG053867)
- 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
- Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
- Keywords
- non-rigid registration, CT-MRI registration, paired training data, multimodal image fusion, deep learning registration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
