SVF-Net: Learning Deformable Image Registration Using Shape Matching

U-Net: Convolutional Networks for Biomedical Image Segmentation

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Fully convolutional networks for semantic segmentation

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Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms

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A Log-Euclidean Framework for Statistics on Diffeomorphisms

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Morphometry of anatomical shape complexes with dense deformations and sparse parameters

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A physics-based coordinate transformation for 3-D image matching

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LCC-Demons: A robust and accurate symmetric diffeomorphic registration algorithm

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Fast Predictive Image Registration

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Computational analysis of LDDMM for brain mapping

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Automatic Segmentation of the Myocardium in Cine MR Images Using Deformable Registration

Jolly, M., Guetter, C., Lu, X., et al. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-28326-0_10 · Cited by 49

Deep learning for registration of high-resolution 3D brain images

Nazib, A. (2020) · Queensland University of Technology · doi:10.5204/thesis.eprints.204293

Constraining Volume Change in Learned Image Registration for Lung CTs.Preprint

Hering, A., Häger, S., Moltz, J. H., Leßmann, N., Heldmann, S., & van Ginneken, B. (2020) · arXiv (Cornell University)

A Joint Super-Resolution and Deformable Registration Network for 3D Brain Images

Lan, S., & Guo, Z. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412553

Rigid Image Registration Based on Graph Matching

Lei, Z., Hu, J., & Ye, B. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-78615-1_26

Cardiovascular Applications of Artificial Intelligence in Research, Diagnosis, and Disease Management

Rajagopalan, V., & Cao, H. (2021) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-7998-8455-2.ch004

A Survey on Deep Learning-Based Diffeomorphic Mapping

Yang, H., Lyu, J., Tam, R. C., & Tang, X. (2022) · Springer eBooks · doi:10.1007/978-3-030-03009-4_108-1

Registration: 2D/3D rigid registration

Liao, H., Zhou, S., & Luo, J. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-824383-1.00014-9

A deep neural network-based distortion registration technique for astronomical images

Zhao, G., Li, J., Luo, L., & Cheng, H. (2023) · Tenth International Conference on Information Optics and Photonics · doi:10.1117/12.3000016

Voxelmorph Learns to Pay Attention

Tousi, S. M. A., Khoramdel, J., Borhani, Y., Shojaei, S., & Nikoofard, A. (2023) · RSI International Conference on Robotics and Mechatronics (ICRoM) · doi:10.1109/icrom60803.2023.10412433

Nonrigid registration method for longitudinal chest CT images in COVID-19

Iwao, Y., Kawata, N., Sekiguchi, Y., & Haneishi, H. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e37272

Alignment of multimodal rigid cardiac angiography images with an improved particle swarm algorithm

Wang, R., & Zhang, B. (2024) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2024-2992

Learning to Estimate Motion Between Non-adjacent Frames in Cardiac Cine MRI Data: A Fusion Approach

Portal, N., Dietenbeck, T., Khan, S., et al. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-78195-7_15

Lddmm-Gan: Diffeomorphic Image Registration with Unsupervised Generative Adversarial NetworksPreprint

Ramon-Julvez, U., Hernandez, M., & Mayordomo, E. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.5063931

A novel image registration hyper spectral classification method for multi-scale image segmentation based on morphology and attributes

Ramakoteswararao, S., Kumari, P. R., Veenanand, K., & Lakshmi, G. (2025) · AIP conference proceedings · doi:10.1063/5.0241878

Lightweight cross‐resolution coarse‐to‐fine network for efficient deformable medical image registration

Liu, J., Shen, N., Wang, W., Li, X., Wang, W., Yuan, Y., Tian, Y., Luo, G., & Wang, K. (2025) · Medical Physics · doi:10.1002/mp.17827

Unsupervised Learning-Based Large Deformation Diffeomorphic Metric Mapping for Fast Image Registration

Wu, J., & Gong, K. (2025) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi60581.2025.10981122

Boosting Medical Image Registration Network Inherently via Collaborative Learning

Hu, B., Dong, G., Zhang, Y., & Xiong, Z. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-91721-9_6

INR-LDDMM:Implicit Neural Representations for Large Deformation Diffeomorphic Metric Mapping No. (will be inserted by the editor)Preprint

Hernández, M., & Rodriguez-Sanz, S. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5459121

Register Anything: Estimating “Corresponding Prompts” for Segment Anything Model

Huang, S., Xu, T., Wen, Y., Barratt, D. C., & Hu, Y. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-04965-0_44

Global-aware multi-scale fusion network for unsupervised non-rigid medical image registration

Zhang, Q., Luan, C., Duan, J., et al. (2025) · Optics & Laser Technology · doi:10.1016/j.optlastec.2025.114437

Small Object Detection via Frequency-Based Multi-modal Fusion

Teng, S., Li, Y., Gong, X., et al. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-6950-2_28

An Effective Non-Rigid Registration Approach for Ultrasound Images Based on the Improved Variational Model of Intensity, Local Phase Information and Descriptor Matching

Zhang, K., Xing, J.-M., & Xiao, Q. (2026) · Journal of Imaging · doi:10.3390/jimaging12040156

Towards the generation of glioblastoma atlases with deep learning methods : Tumor segmentation and metamorphic image registration

Maillard, M. (2023) · doi:10.70675/fc2a0f91zd2f6z47e5za003z3896c31bed02

Image-based guidance of a transesophageal HIFU probe for the treatment of cardiac arrhythmias

Dahman, B. (2022) · doi:10.70675/2617e2bfz5fedz4d50z940dz2e884cda0669

Automatic analysis of cardiac function with artificial intelligence : multimodal approach for portable echocardiographic devices

Yang, Y. (2023) · doi:10.70675/e5ad2298z0bf7z4fe8za059z7fba326f7e8d

PromptReg: Interactive Registration by “Corresponding Prompts” for Segment Anything Model (SAM)

Huang, S., Xu, T., Li, J., Saeed, S. U., Shen, Z., Barratt, D. C., & Hu, Y. (2026) · IEEE Transactions on Image Processing · doi:10.1109/tip.2026.3683270

PSIN-CIR: Progressive Spatial Interleaving Network for Cardiac MRI Image Registration

Wang, H., Song, C., Huang, J., Liu, Y., & Zhang, J. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-3513-1_40

BioDeformUNet: A Deep Learning Model for Biomechanically Informed Liver Image RegistrationPreprint

Zhang, X., O'Connor, C., Castelo, A. H., et al. (2026) · medRxiv · doi:10.64898/2026.08.03.26359612

Multimodal Characterization of Atrial Fibrillation: From Patient-Specific Anatomy and Electrophysiology to Standardized Atrial Mapping

Wang, T., Zou, Q., & Yang, H. (2026) · Tomography · doi:10.3390/tomography12090132

Crossweaver: Towards Efficient Cross-Modal Interweaving and Decoupling for Weakly-Aligned Multispectral Object Detection

Yang, H., Fang, J., Zhu, Y., Zhao, X., Guo, Y., Zhang, X., Hu, X., Yang, X., & Ming, Q. (2026) · doi:10.1109/cvprf71909.2026.00611

Parametrization of effective sizes of cirrus‐cloud particles and its verification against observations

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Parametrization of effective sizes of cirrus-cloud particles and its verification against observations

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An improvement of parametrization of short-wave radiation at the sea surface on the basis of direct measurements in the Atlantic

Aleksandrova, M., Gulev, S., & Sinitsyn, А. V. (2007) · Russian Meteorology and Hydrology · doi:10.3103/s1068373907040048 · Cited by 35

A new parametrization for the radiative properties of ice crystals: Comparison with existing schemes and impact in a GCM

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Parametrization of indecomposable modules

Xue, S. (2011) · Scientia Sinica Mathematica