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Reconstruction of spectra from truncated free induction decays by deep learning in proton magnetic resonance spectroscopy

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Enhanced Deep-Learning-Based Magnetic Resonance Image Reconstruction by Leveraging Prior Subject-Specific Brain Imaging: Proof-of-Concept Using a Cohort of Presumed Normal Subjects

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DEep learning‐based rapid Spiral Image REconstruction (DESIRE) for high‐resolution spiral first‐pass myocardial perfusion imaging

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Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks

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Regularization by Multiple Dual Frames for Compressed Sensing Magnetic Resonance Imaging with Convergence Analysis

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Highly accelerated free‐breathing real‐time phase contrast cardiovascular MRI via complex‐difference deep learning

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Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image Enhancement

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A Comprehensive Evaluation of Deep Learning Models on Knee MRIs for the Diagnosis and Classification of Meniscal Tears: A Systematic Review and Meta-Analysis

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USB-Net: Unfolding Split Bregman Method With Multi-Phase Feature Integration for Compressive Imaging

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Model-Driven Deep Attention Network for Ultra-fast Compressive Sensing MRI Guided by Cross-contrast MR Image

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A k‐space‐to‐image reconstruction network for MRI using recurrent neural network

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An inline deep learning based free-breathing ECG-free cine for exercise cardiovascular magnetic resonance

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Parallel non-Cartesian spatial-temporal dictionary learning neural networks (stDLNN) for accelerating 4D-MRI

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MHAN: Multi-Stage Hybrid Attention Network for MRI reconstruction and super-resolution

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The state-of-the-art in cardiac MRI reconstruction: Results of the CMRxRecon challenge in MICCAI 2023

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High-dimensional embedding network derived prior for compressive sensing MRI reconstruction

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Artificial Intelligence in Health in 2018: New Opportunities, Challenges, and Practical Implications

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Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness

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DeepSENSE: Learning coil sensitivity functions for SENSE reconstruction using deep learning

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Residual RAKI: A hybrid linear and non-linear approach for scan-specific k-space deep learning

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HIWDNet: A hybrid image-wavelet domain network for fast magnetic resonance image reconstruction

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Accelerated two‐dimensional phase‐contrast for cardiovascular MRI using deep learning‐based reconstruction with complex difference estimation

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Signal intensity informed multi‐coil encoding operator for physics‐guided deep learning reconstruction of highly accelerated myocardial perfusion CMR

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Accelerated T2-weighted MRI of the liver at 3 T using a single-shot technique with deep learning-based image reconstruction: impact on the image quality and lesion detection

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Fast Multi-Contrast MRI Acquisition by Optimal Sampling of Information Complementary to Pre-Acquired MRI Contrast

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Magnetic resonance shoulder imaging using deep learning–based algorithm

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Denoising auto-encoding priors in undecimated wavelet domain for MR image reconstruction

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Efficient structurally-strengthened generative adversarial network for MRI reconstruction

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Deep residual U-net with input of static structural responses for efficient U* load transfer path analysis

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The role of artificial intelligence in cardiovascular magnetic resonance imaging

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Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction

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Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T

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End-to-End Deep Learning of Non-rigid Groupwise Registration and Reconstruction of Dynamic MRI

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Accelerated respiratory‐resolved 4D‐MRI with separable spatio‐temporal neural networks

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3D cine-magnetic resonance imaging using spatial and temporal implicit neural representation learning (STINR-MR)

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Zero‐DeepSub: Zero‐shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D‐QALAS

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Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics

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Putting machine learning into motion: applications in cardiovascular imaging

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A Multimodal Dense U-Net For Accelerating Multiple Sclerosis MRI

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Artificial neural network for Slice Encoding for Metal Artifact Correction (SEMAC) MRI

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Attention-Based MultiOffset Deep Learning Reconstruction of Chemical Exchange Saturation Transfer (AMO-CEST) MRI

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Image Reconstruction in Dynamic Inverse Problems with Temporal Models

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Dynamic Imaging Using Deep Bi-Linear Unsupervised Representation (DEBLUR)

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Deep, deep learning with BART

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Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling

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Usefulness of Breath-Hold Fat-Suppressed T2-Weighted Images With Deep Learning–Based Reconstruction of the Liver

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Memory-Efficient Model-Based Deep Learning With Convergence and Robustness Guarantees

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ViGU: Vision GNN U-Net for fast MRI

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SPICER: Self‐supervised learning for MRI with automatic coil sensitivity estimation and reconstruction

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Neural‐network‐based regularization methods for inverse problems in imaging

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Recurrent inference machines for accelerated MRI reconstruction.

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Accelerated Coronary Mri Using 3D Spirit-Raki With Sparsity Regularization

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Dynamic MRI of the abdomen using parallel non‐Cartesian convolutional recurrent neural networks

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20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction

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Data- and Physics-Driven Deep Learning Based Reconstruction for Fast MRI: Fundamentals and Methodologies

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Scientific Image Restoration Anywhere

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Dual-Encoder-Unet For Fast Mri Reconstruction

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An artificial intelligence‐accelerated 2‐minute multi‐shot echo planar imaging protocol for comprehensive high‐quality clinical brain imaging

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Complexities of deep learning-based undersampled MR image reconstruction

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Machine Learning in Neurooncology Imaging: From Study Request to Diagnosis and Treatment

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Accelerated white matter lesion analysis based on simultaneous T1 and T2∗ quantification using magnetic resonance fingerprinting and deep learning

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Data-Consistent Non-Cartesian Deep Subspace Learning for Efficient Dynamic MR Image Reconstruction

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Rethinking Deep Unrolled Model for Accelerated MRI Reconstruction

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Deep Learning Application for Analyzing of Constituents and Their Correlations in the Interpretations of Medical Images

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High fidelity deep learning‐based MRI reconstruction with instance‐wise discriminative feature matching loss

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A financial risk identification model based on artificial intelligence

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Real-time MRI motion estimation through an unsupervised k-space-driven deformable registration network (KS-RegNet)

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Artificial intelligence in cardiac magnetic resonance fingerprinting

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Multi‐parametric MRI for radiotherapy simulation

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Accurate MRI Reconstruction via Multi-Domain Recurrent Networks

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A generalized dual-domain generative framework with hierarchical consistency for medical image reconstruction and synthesis

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