Quantitative MRI

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

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Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

17 shown of 17 papers with code (53 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• MBSS-T1: Model-Based Subject-Specific Self-Supervised Motion Correction for Robust Cardiac T1 Mapping
  21 Aug 2024 2 repositories listed
  Traditional methods, relying on breath-hold sequences and cardiac triggering based on an ECG signal, face challenges with patient compliance, limiting their effectiveness.
• A unified model for reconstruction and R2* mapping of accelerated 7T data using the quantitative recurrent inference machine
  12 Oct 2022 2 repositories listed
  With increasing acceleration factor, an increasing reduction in the reconstruction error was observed, pointing to a larger benefit for sparser data.
• Unified 3D MRI Representations via Sequence-Invariant Contrastive Learning
  21 Jan 2025 1 repository listed
  Self-supervised deep learning has accelerated 2D natural image analysis but remains difficult to translate into 3D MRI, where data are scarce and pre-trained 2D backbones cannot capture volumetric context.
• Domain-Agnostic Stroke Lesion Segmentation Using Physics-Constrained Synthetic Data
  4 Dec 2024 1 repository listed
  Segmenting stroke lesions in MRI is challenging due to diverse acquisition protocols that limit model generalisability.
• MRI Parameter Mapping via Gaussian Mixture VAE: Breaking the Assumption of Independent Pixels
  16 Nov 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  We demonstrate that our approach outperforms current model fitting techniques in dMRI simulations and real data.
• Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI
  13 Mar 2024 1 repository listed
  We demonstrate the potential of PHIMO for the application of T2* quantification from gradient echo MRI, which is particularly sensitive to motion due to its sensitivity to magnetic field inhomogeneities.
• Relaxometry Guided Quantitative Cardiac Magnetic Resonance Image Reconstruction
  1 Mar 2024 1 repository listed
  Deep learning-based methods have achieved prestigious performance for magnetic resonance imaging (MRI) reconstruction, enabling fast imaging for many clinical applications.
• NLCG-Net: A Model-Based Zero-Shot Learning Framework for Undersampled Quantitative MRI Reconstruction
  22 Jan 2024 1 repository listed
  Typical quantitative MRI (qMRI) methods estimate parameter maps after image reconstructing, which is prone to biases and error propagation.
• Zero-DeepSub: Zero-Shot Deep Subspace Reconstruction for Rapid Multiparametric Quantitative MRI Using 3D-QALAS
  4 Jul 2023 1 repository listed
  Using an ISMRM/NIST system phantom, the accuracy and reproducibility of the T1 and T2 maps estimated using the proposed methods were evaluated by comparing them with reference techniques.
• PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction
  19 Jun 2023 1 repository listed
  While various learned and non-learned approaches have been proposed, the existing learned methods fail to fully exploit the prior knowledge about the underlying MR physics, i.
• Choice of training label matters: how to best use deep learning for quantitative MRI parameter estimation
  11 May 2022 1 repository listed
  Self-supervised approaches, sometimes referred to as unsupervised, have been loosely based on auto-encoders, whereas supervised methods have, to date, been trained on groundtruth labels.
• Progressive Subsampling for Oversampled Data -- Application to Quantitative MRI
  17 Mar 2022 1 repository listed
  We build upon a recent dual-network approach that won the MICCAI MUlti-DIffusion (MUDI) quantitative MRI measurement sampling-reconstruction challenge, but suffers from deep learning training instability, by subsampling…
• A Plug-and-Play Approach to Multiparametric Quantitative MRI: Image Reconstruction using Pre-Trained Deep Denoisers
  10 Feb 2022 1 repository listed
  This paper proposes an iterative deep learning plug-and-play reconstruction approach to MRF which is adaptive to the forward acquisition process.
• Improving accuracy and uncertainty quantification of deep learning based quantitative MRI using Monte Carlo dropout
  2 Dec 2021 1 repository listed
  Dropout is conventionally used during the training phase as regularization method and for quantifying uncertainty in deep learning.
• Cramér-Rao bound-informed training of neural networks for quantitative MRI
  22 Sep 2021 1 repository listed
  We find, however, that in heterogeneous parameter spaces, i.
• Compressive MRI quantification using convex spatiotemporal priors and deep auto-encoders
  23 Jan 2020 1 repository listed
  We propose a dictionary-matching-free pipeline for multi-parametric quantitative MRI image computing.
• CoverBLIP: accelerated and scalable iterative matched-filtering for Magnetic Resonance Fingerprint reconstruction
  3 Oct 2018 1 repository listed
  Current popular methods for Magnetic Resonance Fingerprint (MRF) recovery are bottlenecked by the heavy computations of a matched-filtering step due to the growing size and complexity of the fingerprint dictionaries in…

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.