Non-rigid Craniofacial 2D-3D Registration Using CNN-Based Regression

Deep Residual Learning for Image Recognition

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Deep learning in medical image analysis

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A CNN Regression Approach for Real-Time 2D/3D Registration

Miao, S., Wang, Z. J., & Liao, R. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2521800 · Cited by 514 · see citing works

Anisotropic Diffusion

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Non-rigid free-form 2D–3D registration using a B-spline-based statistical deformation model

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Effect of segmentation errors on 3D-to-2D registration of implant models in X-ray images

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Personalized X-Ray Reconstruction of the Proximal Femur via Intensity-Based Non-rigid 2D-3D Registration

Guoyan Zheng, A. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-23629-7_73 · Cited by 34 · see citing works

Segmentation-Driven 2D-3D Registration for Abdominal Catheter Interventions

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3D bone mineral density distribution and shape reconstruction of the proximal femur from a single simulated DXA image: an in vitro study

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Effective incorporating spatial information in a mutual information based 3D–2D registration of a CT volume to X-ray images

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2D-3D Rigid-Body Registration of X-Ray Fluoroscopy and CT Images

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3D volumetric intensity reconsturction from 2D x-ray images using partial least squares regression

Zheng, G. (2013) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2013.6556762 · Cited by 18 · see citing works

Volumetric reconstruction of craniofacial structures from 2D lateral cephalograms by regression forest

Pei, Y., Dai, F., Xu, T., Zha, H., & Ma, G. (2016) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2016.7533121 · Cited by 7 · see citing works

Deep learning in medical image registration: a review

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Medical image registration using deep neural networks: A comprehensive review

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The Impact of Machine Learning on 2D/3D Registration for Image-Guided Interventions: A Systematic Review and Perspective

Unberath, M., Gao, C., Hu, Y., Judish, M., Taylor, R. H., Armand, M., & Grupp, R. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.716007 · Cited by 102 · see citing works

3-D Reconstruction in Canonical Co-Ordinate Space From Arbitrarily Oriented 2-D Images

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A review of deep learning-based deformable medical image registration

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An application independent review of multimodal 3D registration methods

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Unsupervised End-to-End Brain Tumor Magnetic Resonance Image Registration Using RBCNN: Rigid Transformation, B-Spline Transformation and Convolutional Neural Network

Senthil Pandi, S., & Krishnan, M. A. (2021) · Current Medical Imaging Formerly Current Medical Imaging Reviews · doi:10.2174/1573405617666210806125526 · Cited by 32 · see citing works

Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry

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Automatic craniofacial registration based on radial curves

Huang, R., Zhao, J., Duan, F., Li, X. S., Liu, C., Deng, X., Pan, Z., Wu, Z., & Zhou, M. (2019) · Computers & Graphics · doi:10.1016/j.cag.2019.05.026 · Cited by 14 · see citing works

Non-Rigid 2D-3D Registration Using Convolutional Autoencoders

Li, P., Pei, Y., Guo, Y., Ma, G., Xu, T., & Zha, H. (2020) · 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi45749.2020.9098602 · Cited by 13 · see citing works

Deformable CT image registration via a dual feasible neural network

Lei, Y., Fu, Y., Tian, Z., Wang, T., Dai, X., Roper, J. R., Yu, D. S., McDonald, M. W., Bradley, J. D., Liu, T., et al. (2022) · Medical Physics · doi:10.1002/mp.15875 · Cited by 12 · see citing works

Deformable 3D–2D image registration and analysis of global spinal alignment in long‐length intraoperative spine imaging

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LiftReg: Limited Angle 2D/3D Deformable Registration

Tian, L., Lee, Y. Z., Estépar, R. S. J., & Niethammer, M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16446-0_20 · Cited by 7 · see citing works

Deformable 3D-2D registration for high-precision guidance and verification of neuroelectrode placement

Uneri, A., Wu, P., Jones, C. K., Vagdargi, P., Han, R., Helm, P. A., Luciano, M. G., Anderson, W. S., & Siewerdsen, J. H. (2021) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ac2f89 · Cited by 6 · see citing works

Breathing-Compensated Neural Networks for Real Time C-Arm Pose Estimation in Lung CT-Fluoroscopy Registration

Lee, B. C., Sinha, A., Varble, N., Pritchard, W. F., Karanian, J. W., Wood, B. J., & Bydlon, T. M. (2022) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi52829.2022.9761705 · Cited by 6 · see citing works

CR-Net: A robust craniofacial registration network by introducing Wasserstein distance constraint and geometric attention mechanism

Dai, Z., Zhao, J., Deng, X., Duan, F., Li, D., Pan, Z., & Zhou, M. (2023) · Computers & Graphics · doi:10.1016/j.cag.2023.08.015 · Cited by 6 · 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

Temporal Consistent 2D-3D Registration of Lateral Cephalograms and Cone-Beam Computed Tomography Images

Zhang, Y., Pei, Y., Qin, H., Guo, Y., Ma, G., Xu, T., & Zha, H. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00919-9_43 · Cited by 6 · see citing works

Deformable 3D/3D CT-to-digital-tomosynthesis image registration in image-guided bronchoscopy interventions

Saad, F., Frysch, R., Saalfeld, S., Kellnberger, S., Schulz, J., Fahrig, R., Bhadra, K., Nürnberger, A., & Rose, G. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108199 · Cited by 4 · see citing works

3D Volume Reconstruction from Single Lateral X-Ray Image via Cross-Modal Discrete Embedding Transition

Jiang, Y., Li, P., Zhang, Y., Pei, Y., Guo, Y., Xu, T., & Yuan, X. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59861-7_33 · Cited by 3 · see citing works

Deformation field prediction based on a modified loss function with U-Net for non rigid image registration

Bahi, O. E., Qaraai, Y., & Allaoui, A. E. (2025) · Signal Image and Video Processing · doi:10.1007/s11760-025-04452-6 · Cited by 3 · see citing works

Toward Semantically-Consistent Deformable 2D-3D Registration for 3D Craniofacial Structure Estimation From a Single-View Lateral Cephalometric Radiograph

Jiang, Y., Pei, Y., Xu, T., Yuan, X., & Zha, H. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3456251 · Cited by 2 · see citing works

Craniofacial Volumetric Image Estimation From a Lateral Cephalogram Using Cross-Dimensional Discrete Embedding Mapping

Jiang, Y., Pei, Y., Li, P., Zhang, Y., Guo, Y., Fan, Y., Chen, G., Dai, F., Xu, T., Yuan, X., et al. (2022) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2022.3216202 · Cited by 1 · see citing works

Rectal Carcinoma Segmentation Based On Image Pre-processing and Improved U-Net with Residual Block

Runchen, L., Hao, W., He, G., Ahmad, K. M., & Yu, W. (2021) · International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) · doi:10.1109/mlise54096.2021.00034 · Cited by 1 · see citing works

Deep learning-based longitudinal CT registration for anatomy variation assessment during radiotherapy

Fu, Y., Lei, Y., Tian, Z., Wang, T., Dai, X., Zhou, J., McDonald, M. W., Bradley, J. D., Liu, T., & Yang, X. (2022) · SPIE Medical Imaging: Computer-Aided Diagnosis · doi:10.1117/12.2611901

XSynthMorph: Generative-Guided Deformation for Unsupervised Ill-Posed Volumetric Recovery

Cafaro, A., Leroy, A., Beldjoudi, G., Maury, P., Robert, C., Deutsch, É., Grégoire, V., Lepetit, V., & Nikos Paragios, A. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73480-9_2

Non-Rigid 2D-3D Registration Using Convolutional Autoencoders

Li, P., Pei, Y., Guo, Y., Ma, G., Xu, T., & Zha, H. (2020) · 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi45749.2020.9098602 · Cited by 13 · see citing works

A CNN Regression Approach for Real-Time 2D/3D Registration

Miao, S., Wang, Z. J., & Liao, R. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2521800 · Cited by 514 · see citing works

Real-time 2D/3D registration via CNN regression

Miao, S., Wang, Z. J., Zheng, Y., & Liao, R. (2016) · 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2016.7493536 · Cited by 101 · see citing works

Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients

Gu, W., Gao, C., Grupp, R., Fotouhi, J., & Unberath, M. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-59861-7_29 · Cited by 16 · see citing works

Convolutional Neural Networks for Robust and Real-Time 2-D/3-D Registration

Miao, S., Wang, J. Z., & Liao, R. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-810408-8.00016-x · Cited by 8 · see citing works