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Image Super-Resolution Using Deep Convolutional Networks

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Attention incorporated network for sharing low-rank, image and k-space information during MR image reconstruction to achieve single breath-hold cardiac Cine imaging

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Improved simultaneous multislice cardiac MRI using readout concatenated k‐space SPIRiT (ROCK‐SPIRiT)

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Benchmarking Deep Nets MRI Reconstruction Models on the Fastmri Publicly Available Dataset

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$Σ$-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image ReconstructionPreprint

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A deep error correction network for compressed sensing MRI

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Rapid Reconstruction of Four-dimensional MR Angiography of the Thoracic Aorta Using a Convolutional Neural Network

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Identifying the regional substrates predictive of Alzheimer's disease progression through a convolutional neural network model and occlusion

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Deep unfolding architecture for MRI reconstruction enhanced by adaptive noise maps

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Learned Tensor Low-CP-Rank and Bloch Response Manifold Priors for Non-Cartesian MRF Reconstruction

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Self-Supervised Deep Equilibrium Models With Theoretical Guarantees and Applications to MRI Reconstruction

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CS-MRI Reconstruction Using an Improved GAN with Dilated Residual Networks and Channel Attention Mechanism

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Deep learning-based diffusion tensor cardiac magnetic resonance reconstruction: a comparison study

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HFGN: High-Frequency residual Feature Guided Network for fast MRI reconstruction

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Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction

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Fault diagnosis of gas turbine based on feature fusion cascade neural network

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Multi-Contrast Mr Reconstruction with Enhanced Denoising Autoencoder Prior Learning

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Groupwise Non-Rigid Registration with Deep Learning: An Affordable Solution Applied to 2D Cardiac Cine MRI Reconstruction

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A dual-task dual-domain model for blind MRI reconstruction

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Optimizing multicontrast MRI reconstruction with shareable feature aggregation and selection

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Deep artifact suppression for spiral real-time phase contrast cardiac magnetic resonance imaging in congenital heart disease

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Multiscale U-net-based accelerated magnetic resonance imaging reconstruction

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GRASPNET: Fast spatiotemporal deep learning reconstruction of golden‐angle radial data for free‐breathing dynamic contrast‐enhanced magnetic resonance imaging

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An inner-loop free solution to inverse problems using deep neural networksPreprint

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VS-Net: Variable splitting network for accelerated parallel MRI reconstructionPreprint

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SelfCoLearn: Self-Supervised Collaborative Learning for Accelerating Dynamic MR Imaging

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A Joint Group Sparsity-based deep learning for multi-contrast MRI reconstruction

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From Compressed‐Sensing to Deep Learning MR : Comparative Biventricular Cardiac Function Analysis in a Patient Cohort

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WKGM: weighted k‐space generative model for parallel imaging reconstruction

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What Do AEs Learn? Challenging Common Assumptions in Unsupervised Anomaly Detection

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Highly‐accelerated CEST MRI using frequency‐offset‐dependent k‐space sampling and deep‐learning reconstruction

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Prospective Deployment of Deep Learning Reconstruction Facilitates Highly Accelerated Upper Abdominal MRI

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Deep Learning For Mri Reconstruction Using A Novel Projection Based Cascaded Network

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Sparse Anett For Solving Inverse Problems With Deep Learning

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Parallel imaging with a combination of sensitivity encoding and generative adversarial networks

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Spatial orthogonal attention generative adversarial network for MRI reconstruction

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Temporally aware volumetric generative adversarial network‐based MR image reconstruction with simultaneous respiratory motion compensation: Initial feasibility in 3D dynamic cine cardiac MRI

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Simultaneous image reconstruction and lesion segmentation in accelerated MRI using multitasking learning

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Localized Motion Artifact Reduction on Brain MRI Using Deep Learning with Effective Data Augmentation Techniques

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A selective region-based detection and tracking approach towards the recognition of dynamic bare hand gesture using deep neural network

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Accelerating susceptibility-weighted imaging with deep learning by complex-valued convolutional neural network (ComplexNet): validation in clinical brain imaging

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Real‐time cardiac MRI using an undersampled spiral k‐space trajectory and a reconstruction based on a variational network

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Joint optimization of Cartesian sampling patterns and reconstruction for single‐contrast and multi‐contrast fast magnetic resonance imaging

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Deep supervised dictionary learning by algorithm unrolling—Application to fast 2D dynamic MR image reconstruction

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Adaptive channel-modulated personalized federated learning for magnetic resonance image reconstruction

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Accelerated Phase Contrast Magnetic Resonance Imaging via Deep Learning

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Automatic classification of spinal osteosarcoma and giant cell tumor of bone using optimized DenseNet

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Efficient 3D Low-Discrepancy ${k}$ -Space Sampling Using Highly Adaptable Seiffert Spirals

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Self-supervised Dynamic MRI Reconstruction

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FlowRAU-Net: Accelerated 4D Flow MRI of Aortic Valvular Flows With a Deep 2D Residual Attention Network

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Single-breath-hold T2WI MRI with artificial intelligence-assisted technique in liver imaging: As compared with conventional respiratory-triggered T2WI

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A novel hybrid generative adversarial network for CT and MRI super-resolution reconstruction

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AutoSamp: Autoencoding k-Space Sampling via Variational Information Maximization for 3D MRI

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Accelerated Wideband Myocardial Perfusion Pulse Sequence with Compressed Sensing Reconstruction for Myocardial Blood Flow Quantification in Patients with a Cardiac Implantable Electronic Device

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Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge

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Strategies for Sudden Cardiac Death Prevention

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LSTM‐Based RNN Framework to Remove Motion Artifacts in Dynamic Multicontrast MR Images with Registration Model

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AI in Health Science: A Perspective

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A unified model for reconstruction and R 2 * mapping of accelerated 7T data using the quantitative recurrent inference machine

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Medical Imaging Synthesis using Deep Learning and its Clinical Applications: A ReviewPreprint

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An inner-loop free solution to inverse problems using deep neural networks

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Deep Learning Based Compressive Sensing for Image Reconstruction and Inference

Pavitra, V., Dutt, V. B. S. S. I., & Rajkumar, G. V. S. (2022) · IEEE International Conference for Convergence in Technology (I2CT) · doi:10.1109/i2ct54291.2022.9824890 · Cited by 13

LARO: Learned acquisition and reconstruction optimization to accelerate quantitative susceptibility mapping

Zhang, J., Spincemaille, P., Zhang, H., Nguyen, T. D., Li, C., Li, J., Kovanlıkaya, İ., Sabuncu, M. R., & Wang, Y. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119886 · Cited by 13

High-Fidelity MRI Reconstruction Using Adaptive Spatial Attention Selection and Deep Data Consistency Prior

Liu, J., Qin, C., & Yaghoobi, M. (2023) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2023.3258839 · Cited by 13

PtychoDV: Vision Transformer-Based Deep Unrolling Network for Ptychographic Image Reconstruction

Gan, W., Zhai, Q., McCann, M. T., García–Cardona, C., Kamilov, U. S., & Wohlberg, B. E. (2024) · IEEE Open Journal of Signal Processing · doi:10.1109/ojsp.2024.3375276 · Cited by 13

IWNeXt: an image-wavelet domain ConvNeXt-based network for self-supervised multi-contrast MRI reconstruction

Yan, Y., Yang, T., Jiao, C., Yang, A., & Miao, J. (2024) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ad33b4 · Cited by 13

CineVN: Variational network reconstruction for rapid functional cardiac cine MRI

Vornehm, M., Wetzl, J., Giese, D., Fürnrohr, F., Pang, J., Chow, K., Gebker, R., Ahmad, R., & Knöll, F. (2024) · Magnetic Resonance in Medicine · doi:10.1002/mrm.30260 · Cited by 13

Accelerating MR Imaging via Deep Chambolle-Pock Network

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A feature‐based convolutional neural network for reconstruction of interventional MRI

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Ensure: Ensemble Stein’s Unbiased Risk Estimator for Unsupervised Learning

Aggarwal, H. K., Pramanik, A., & Jacob, M. (2021) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp39728.2021.9414513 · Cited by 13

Learning to autofocus in whole slide imaging via physics-guided deep cascade networks

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SR-Net: A sequence offset fusion net and refine net for undersampled multislice MR image reconstruction

Xiao, Z., Du, N., Liu, J., & Zhang, W. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.105997 · Cited by 13

Feasibility of compressed sensing technique for isotropic dynamic contrast-enhanced liver magnetic resonance imaging

Sun, W., Wang, W., Zhu, K., Chen, C., Wen, X., Zeng, M., & Rao, S. (2021) · European Journal of Radiology · doi:10.1016/j.ejrad.2021.109729 · Cited by 13

Assessment of data consistency through cascades of independently recurrent inference machines for fast and robust accelerated MRI reconstruction

Karkalousos, D., Noteboom, S., Hulst, H. E., Vos, F. M., & Caan, M. W. A. (2022) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ac6cc2 · Cited by 13

Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep Learned Prior

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Low-Rank Tensor Subspace Decomposition With Weighted Group Sparsity for the Acceleration of Non-Cartesian Dynamic MRI

Liu, B., Ding, Z., Zhang, Y.-F., She, H., & Du, Y. P. (2022) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2022.3200709 · Cited by 13

Referenceless distortion correction of gradient-echo echo-planar imaging under inhomogeneous magnetic fields based on a deep convolutional neural network

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Convolutional Neural Network for Sparse Reconstruction of MR Images Interposed with Gaussian Noise

Manimala, M. V. R., Naidu, C. D., & Prasad, M. N. G. (2019) · Journal of Circuits Systems and Computers · doi:10.1142/s0218126620501169 · Cited by 13

Brain Segmentation from k-Space with End-to-End Recurrent Attention Network

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Implicit neural representation for medical image reconstruction

Zhu, Y., Liu, Y., Zhang, Y., & Liang, D. (2025) · Physics in Medicine and Biology · doi:10.1088/1361-6560/addfa5 · Cited by 14

Deformation-Compensated Learning for Image Reconstruction Without Ground Truth

Gan, W., Sun, Y., Eldeniz, C., Liu, J., An, H., & Kamilov, U. S. (2022) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2022.3163018 · Cited by 12

An unsupervised region of interest extraction model for tau PET images and its application in the diagnosis of Alzheimer's disease

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Unsupervised Deep Basis Pursuit Based Resolution Enhancement for Forward Looking MIMO SAR Imaging

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HyperSLICE : HyperBand optimized spiral for low‐latency interactive cardiac examination

Jaubert, O., Montalt‐Tordera, J., Knight, D. S., Arridge, S., Steeden, J. A., & Muthurangu, V. (2023) · Magnetic Resonance in Medicine · doi:10.1002/mrm.29855 · Cited by 12

T 2 LR-Net: An unrolling network learning transformed tensor low-rank prior for dynamic MR image reconstruction

Zhang, Y., Li, P., & Hu, Y. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108034 · Cited by 12

Adaptive Knowledge Distillation for High-Quality Unsupervised MRI Reconstruction With Model-Driven Priors

Wu, Z., & Li, X. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3365784 · Cited by 12

Image Reconstruction for Accelerated MR Scan With Faster Fourier Convolutional Neural Networks

Liu, X., Pang, Y., Sun, X., Liu, Y., Hou, Y., Wang, Z., & Li, X. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3388970 · Cited by 15

CRNN-Refined Spatiotemporal Transformer for Dynamic MRI reconstruction

Wang, B., Lian, Y., Xiong, X., Han, H., & Liu, Z. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.109133 · Cited by 12

Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling

Elata, N., Michaeli, T., & Elad, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73229-4_17 · Cited by 12

CL-MRI: Self-Supervised contrastive learning to improve the accuracy of undersampled MRI reconstruction

Ekanayake, M. M., Chen, Z., Harandi, M. T., Egan, G. F., & Chen, Z. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.107185 · Cited by 12

Accelerated Simultaneous Multi-Slice MRI using Subject-Specific Convolutional Neural Networks

Zhang, C., Moeller, S., Weingärtner, S., Uǧurbil, K., & Akçakaya, M. (2018) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/acssc.2018.8645313 · Cited by 12

Deep convolution neural networks based artifact suppression in under-sampled radial acquisitions of myocardial T 1 mapping images

Nezafat, M., El-Rewaidy, H., Küçükseymen, S., Hauser, T. H., & Fahmy, A. S. (2020) · Physics in Medicine and Biology · doi:10.1088/1361-6560/abc04f · Cited by 12

Self-Attention-Based Convolutional Neural Networks for Sentence Classification

Lu, W., Duan, Y., & Song, Y. (2020) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/iccc51575.2020.9345092 · Cited by 13

Emerging MRI techniques for molecular and functional phenotyping of the diseased heart

Cheng, H. M. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.1072828 · Cited by 12

Reconstruction of undersampled radial free‐breathing 3D abdominal MRI using stacked convolutional auto‐encoders

Lv, J., Chen, K., Yang, M. Y., Zhang, J., & Wang, X. (2018) · Medical Physics · doi:10.1002/mp.12870 · Cited by 12

Non-learning based deep parallel MRI reconstruction (NLDpMRI)

Yazdanpanah, A. P., Afacan, O., & Warfield, S. K. (2019) · SPIE Medical Imaging: Image Processing · doi:10.1117/12.2511653 · Cited by 12

A Victims Detection Approach for Burning Building Sites Using Convolutional Neural Networks

Jaradat, F. B., & Valles, D. (2020) · IEEE Annual Computing and Communication Workshop and Conference (CCWC) · doi:10.1109/ccwc47524.2020.9031275 · Cited by 12

A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction

Schlemper, J., Caballero, J., Hajnal, J. V., Price, A. N., & Rueckert, D. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-59050-9_51 · Cited by 356

Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction

Qin, C., Schlemper, J., Caballero, J., Price, A. N., Hajnal, J. V., & Rueckert, D. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2863670 · Cited by 606

Hybrid image and k-space deep learning reconstruction exploiting spatio-temporal redundancies for 2D cardiac CINE

Xu, S., Krumm, P., Lingg, A., Qi, H., Hammernik, K., & Küstner, T. (2023) · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · doi:10.58530/2022/0953

Deep Learning Within a Priori Temporal Feature Spaces for Large-Scale Dynamic MR Image Reconstruction: Application to 5-D Cardiac MR Multitasking

Chen, Y., Shaw, J. L., Xie, Y., Li, D., & Christodoulou, A. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-32245-8_55 · Cited by 25

Deep Network Cascade for Dynamic Cardiac MRI Reconstruction With Motion Feature Incorporation and the Fourier Neural Attention

Liu, J., Qin, C., & Yaghoobi, M. (2024) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2024.3402335 · Cited by 4