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Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition

arXiv 1902.03051 ↗First posted 8 Feb 2019cs.CVcited by 55

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Abstract (arXiv)

The goal of MRI reconstruction is to restore a high fidelity image from partially observed measurements. This partial view naturally induces reconstruction uncertainty that can only be reduced by acquiring additional measurements. In this paper, we present a novel method for MRI reconstruction that, at inference time, dynamically selects the measurements to take and iteratively refines the prediction in order to best reduce the reconstruction error and, thus, its uncertainty. We validate our method on a large scale knee MRI dataset, as well as on ImageNet. Results show that (1) our system successfully outperforms active acquisition baselines; (2) our uncertainty estimates correlate with error maps; and (3) our ResNet-based architecture surpasses standard pixel-to-pixel models in the task of MRI reconstruction. The proposed method not only shows high-quality reconstructions but also paves the road towards more applicable solutions for accelerating MRI.

Key facts. Cited by 55 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Feb 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 12; 2022: 11; 2023: 15; 2024: 7; 2025: 3; 2026: 7.

55 papers.

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  1. 2023A Review of Uncertainty Estimation and its Application in Medical Imagingcited by 59
  2. 2023Learning Federated Visual Prompt in Null Space for MRI Reconstructioncited by 40
  3. 2023A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methodscited by 39
  4. 2021Deep reinforcement learning in medical imaging: A literature reviewcited by 34
  5. 2021Active 3D Shape Reconstruction from Vision and Touchcited by 34
  6. 2023A comprehensive survey on deep active learning in medical image analysiscited by 32
  7. 2022DSFormer: A Dual-domain Self-supervised Transformer for Accelerated Multi-contrast MRI Reconstructioncited by 30
  8. 2021A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applicationscited by 24
  9. 2021Uncertainty-Guided Progressive GANs for Medical Image Translationcited by 16
  10. 2021Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image Enhancementcited by 15
  11. 2022ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inferencecited by 15
  12. 2022On learning adaptive acquisition policies for undersampled multi-coil MRI reconstructioncited by 14
38 more
  1. 2021End-to-End Sequential Sampling and Reconstruction for MRIcited by 13
  2. 2021A review and experimental evaluation of deep learning methods for MRI reconstructioncited by 13
  3. 2023Dual-Domain Self-Supervised Learning for Accelerated Non-Cartesian MRI Reconstructioncited by 13
  4. 2023On Retrospective k-space Subsampling schemes For Deep MRI Reconstructioncited by 12
  5. 2024Adaptive Compressed Sensing with Diffusion-Based Posterior Samplingcited by 12
  6. 2022Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networkscited by 11
  7. 2022Dual-Domain Reconstruction Networks with V-Net and K-Net for fast MRIcited by 8
  8. 2024Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Predictioncited by 7
  9. 2022PUERT: Probabilistic Under-sampling and Explicable Reconstruction Network for CS-MRIcited by 5
  10. 2021Towards Robust Active Feature Acquisitioncited by 4
  11. 2023USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolutioncited by 4
  12. 2025Diffusion Active Learning: Towards Data-Driven Experimental Design in Computed Tomographycited by 4
  13. 2022JoJoNet: Joint-contrast and Joint-sampling-and-reconstruction Network for Multi-contrast MRIcited by 3
  14. 2022Active CT Reconstruction with a Learned Sampling Policycited by 3
  15. 2023On the Feasibility of Machine Learning Augmented Magnetic Resonance for Point-of-Care Identification of Diseasecited by 3
  16. 2023PixCUE: Joint Uncertainty Estimation and Image Reconstruction in MRI using Deep Pixel Classificationcited by 3
  17. 2023Learning Task-Specific Strategies for Accelerated MRIcited by 3
  18. 2021Deep MRI Reconstruction with Radial Subsamplingcited by 2
  19. 2021Fast T2w/FLAIR MRI Acquisition by Optimal Sampling of Information Complementary to Pre-acquired T1w MRIcited by 2
  20. 2023Uncertainty Estimation in Contrast-Enhanced MR Image Translation with Multi-Axis Fusioncited by 2
  21. 2024The MRI Scanner as a Diagnostic: Image-less Active Samplingcited by 2
  22. 2024Adaptive Selection of Sampling-Reconstruction in Fourier Compressed Sensingcited by 2
  23. 2021Real-Time Mapping of Tissue Properties for Magnetic Resonance Fingerprintingcited by 1
  24. 2022Active Phase-Encode Selection for Slice-Specific Fast MR Scanning Using a Transformer-Based Deep Reinforcement Learning Frameworkcited by 1
  25. 2022A Path Towards Clinical Adaptation of Accelerated MRIcited by 1
  26. 2023Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothingcited by 1
  27. 2023On the Quantification of Image Reconstruction Uncertainty without Training Datacited by 1
  28. 2024DuDoUniNeXt: Dual-domain unified hybrid model for single and multi-contrast undersampled MRI reconstructioncited by 1
  29. 2025Active Sampling for MRI-based Sequential Decision Makingcited by 1
  30. 2026ReDiff: Reliability-Guided Diffusion for Trustworthy Ultra-Low-Field to High-Field MRI Synthesiscited by 1
  31. 2026SIREM: Speech-Informed MRI Reconstruction with Learned Samplingcited by 1
  32. 2021Unsupervised Embedding Learning from Uncertainty Momentum Modelingcited by 0
  33. 2022L2SR: Learning to Sample and Reconstruct for Accelerated MRI via Reinforcement Learningcited by 0
  34. 2023ALUM: Adversarial Data Uncertainty Modeling from Latent Model Uncertainty Compensationcited by 0
  35. 2023Reinforcement Learning for Sampling on Temporal Medical Imaging Sequencescited by 0
  36. 2024LSST: Learned Single-Shot Trajectory and Reconstruction Network for MR Imagingcited by 0
  37. 2024MS-Glance: Bio-Insipred Non-semantic Context Vectors and their Applications in Supervising Image Reconstructioncited by 0
  38. 2025Adaptive Mask-guided K-space Diffusion for Accelerated MRI Reconstructioncited by 0

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