Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement | Paper Citation Record

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This paper cites Quantitative magnetic resonance imaging of brain anatomy and in vivo histology.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Quantitative magnetic resonance imaging of brain anatomy and in vivo histology

Reference 1

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This paper cites Primary Multiparametric Quantitative Brain MRI: State-of- the-Art Relaxometric and Proton Density Mapping Techniques.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Primary Multiparametric Quantitative Brain MRI: State-of- the-Art Relaxometric and Proton Density Mapping Techniques

Reference 2

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This paper cites Multiparametric Quantitative MRI in Neurological Diseases.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Multiparametric Quantitative MRI in Neurological Diseases

Reference 3

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This paper cites Generalized autocalibrating partially parallel acquisitions (GRAPPA).

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Generalized autocalibrating partially parallel acquisitions (GRAPPA)

Reference 4

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This paper cites SENSE: sensitivity encoding for fast MRI.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement SENSE: sensitivity encoding for fast MRI

Reference 5

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This paper cites Sparse MRI: The application of compressed sensing for rapid MR imaging.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Sparse MRI: The application of compressed sensing for rapid MR imaging

Reference 6

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This paper cites SPIRiT: Iterative Self-consistent Parallel Imaging Reconstruction from Arbitrary k-Space.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement SPIRiT: Iterative Self-consistent Parallel Imaging Reconstruction from Arbitrary k-Space

Reference 7

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This paper cites Compressed sensing reconstruction for magnetic resonance parameter mapping.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Compressed sensing reconstruction for magnetic resonance parameter mapping

Reference 8

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Observation d1862463-c0c6-44b0-bd79-f7a4e88dc828 · outbound

This paper cites T2 mapping from highly undersampled data by reconstruction of principal component coefficient maps using compressed sensing.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement T2 mapping from highly undersampled data by reconstruction of principal component coefficient maps using compressed sensing

Reference 9

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This paper cites Fast MR parameter mapping using k-t principal component analysis.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Fast MR parameter mapping using k-t principal component analysis

Reference 10

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This paper cites Accelerating MR parameter mapping using sparsity-promoting regularization in parametric dimension.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Accelerating MR parameter mapping using sparsity-promoting regularization in parametric dimension

Reference 11

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This paper cites Model-based iterative reconstruction for radial fast spin-echo MRI.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Model-based iterative reconstruction for radial fast spin-echo MRI

Reference 12

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This paper cites Accelerating parameter mapping with a locally low rank constraint.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Accelerating parameter mapping with a locally low rank constraint

Reference 13

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This paper cites Accelerated High-Dimensional MR Imaging With Sparse Sampling Using Low-Rank Tensors.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Accelerated High-Dimensional MR Imaging With Sparse Sampling Using Low-Rank Tensors

Reference 14

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This paper cites Three‐dimensional simultaneous brain mapping of T1, T2, and magnetic susceptibility with MR Multitasking.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Three‐dimensional simultaneous brain mapping of T1, T2, and magnetic susceptibility with MR Multitasking

Reference 15

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This paper cites Echo planar time‐resolved imaging with subspace reconstruction and optimized spatiotemporal encoding.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Echo planar time‐resolved imaging with subspace reconstruction and optimized spatiotemporal encoding

Reference 16

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This paper cites Accelerated MR Parameter Mapping with Low-Rank and Sparsity Constraints.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Accelerated MR Parameter Mapping with Low-Rank and Sparsity Constraints

Reference 17

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This paper cites an unresolved cited work.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 18

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Observation 73c3d7a3-9bcd-4fd6-8893-727d8affe6ef · outbound

This paper cites Deep model-based magnetic resonance parameter mapping network (DOPAMINE) for fast T1 mapping using variable flip angle method.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Deep model-based magnetic resonance parameter mapping network (DOPAMINE) for fast T1 mapping using variable flip angle method

Reference 19

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This paper cites Magnetic resonance fingerprinting.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Magnetic resonance fingerprinting

Reference 20

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This paper cites Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network

Reference 21

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This paper cites MANTIS: Model-Augmented Neural neTwork with Incoherent k-space Sampling for efficient MR parameter mapping.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement MANTIS: Model-Augmented Neural neTwork with Incoherent k-space Sampling for efficient MR parameter mapping

Reference 22

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This paper cites A simultaneous multi-slice T2 mapping framework based on overlapping-echo detachment planar imaging and deep learning reconstruction.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement A simultaneous multi-slice T2 mapping framework based on overlapping-echo detachment planar imaging and deep learning reconstruction

Reference 23

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This paper cites MOdel-Based SyntheTic Data-Driven Learning (MOST-DL): Application in Single-Shot T2 Mapping With Severe Head Motion Using Overlapping-Echo Acquisition.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement MOdel-Based SyntheTic Data-Driven Learning (MOST-DL): Application in Single-Shot T2 Mapping With Severe Head Motion Using Overlapping-Echo Acquisition

Reference 24

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This paper cites Robust Single-Shot T2 Mapping via Multiple Overlapping- Echo Acquisition and Deep Neural Network.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Robust Single-Shot T2 Mapping via Multiple Overlapping- Echo Acquisition and Deep Neural Network

Reference 25

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This paper cites qMTNet: Accelerated quantitative 22 magnetization transfer imaging with artificial neural networks.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement qMTNet: Accelerated quantitative 22 magnetization transfer imaging with artificial neural networks

Reference 26

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This paper cites One for multiple: Physics-informed synthetic data boosts generalizable deep learning for fast MRI reconstruction.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement One for multiple: Physics-informed synthetic data boosts generalizable deep learning for fast MRI reconstruction

Reference 27

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This paper cites Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data

Reference 28

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This paper cites MR fingerprinting Deep RecOnstruction NEtwork (DRONE).

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement MR fingerprinting Deep RecOnstruction NEtwork (DRONE)

Reference 29

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This paper cites SSL-QALAS: Self-Supervised Learning for rapid multiparameter estimation in quantitative MRI using 3D-QALAS.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement SSL-QALAS: Self-Supervised Learning for rapid multiparameter estimation in quantitative MRI using 3D-QALAS

Reference 30

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This paper cites Zero-DeepSub: Zero-shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D-QALAS.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Zero-DeepSub: Zero-shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D-QALAS

Reference 31

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This paper cites Joint MAPLE: Accelerated joint T1 and T2* mapping with scan‐specific self‐supervised networks.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Joint MAPLE: Accelerated joint T1 and T2* mapping with scan‐specific self‐supervised networks

Reference 32

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This paper cites Magnetic resonance parameter mapping using model-guided self-supervised deep learning.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Magnetic resonance parameter mapping using model-guided self-supervised deep learning

Reference 33

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This paper cites Coordinate-based neural representation enabling zero-shot learning for fast 3D multiparametric quantitative MRI.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Coordinate-based neural representation enabling zero-shot learning for fast 3D multiparametric quantitative MRI

Reference 34

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This paper cites High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models

Reference 35

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This paper cites NeRF: representing scenes as neural radiance fields for view synthesis.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement NeRF: representing scenes as neural radiance fields for view synthesis

Reference 36

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This paper cites NeRF-SR: High Quality Neural Radiance Fields using Supersampling.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement NeRF-SR: High Quality Neural Radiance Fields using Supersampling

Reference 37

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This paper cites Improving quantitative MRI using self-supervised deep learning with model reinforcement: Demonstration for rapid T1 mapping.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Improving quantitative MRI using self-supervised deep learning with model reinforcement: Demonstration for rapid T1 mapping

Reference 38

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This paper cites NeX: Real-time View Synthesis with Neural Basis Expansion.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement NeX: Real-time View Synthesis with Neural Basis Expansion

Reference 40

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This paper cites Dynamic CT Reconstruction from Limited Views with Implicit Neural Representations and Parametric Motion Fields.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Dynamic CT Reconstruction from Limited Views with Implicit Neural Representations and Parametric Motion Fields

Reference 42

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This paper cites Recovery of continuous 3D refractive index maps from discrete intensity-only measurements using neural fields.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Recovery of continuous 3D refractive index maps from discrete intensity-only measurements using neural fields

Reference 43

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This paper cites CoIL: Coordinate-Based Internal Learning for Tomographic Imaging.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement CoIL: Coordinate-Based Internal Learning for Tomographic Imaging

Reference 44

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Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 45

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This paper cites an unresolved cited work.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 46

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This paper cites Spatiotemporal Implicit Neural Representation for Unsupervised Dynamic MRI Reconstruction.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Spatiotemporal Implicit Neural Representation for Unsupervised Dynamic MRI Reconstruction

Reference 47

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This paper cites Self-Supervised Coordinate Projection Network for Sparse-View Computed Tomography.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Self-Supervised Coordinate Projection Network for Sparse-View Computed Tomography

Reference 48

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This paper cites IMJ-PLUS: Implicit Representation for Dynamic 24 MRI and Coil Sensitivity Joint Reconstruction Using Low-Rank PLUS Sparse Regularization.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement IMJ-PLUS: Implicit Representation for Dynamic 24 MRI and Coil Sensitivity Joint Reconstruction Using Low-Rank PLUS Sparse Regularization

Reference 49

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Observation 833c9337-5fb9-4d05-8dbe-8be6bce7a38e · outbound

This paper cites Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging

Reference 50

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Observation 848b4a9b-a8d5-4412-8b7b-dbb2e535a466 · outbound

This paper cites Implicit Neural Networks With Fourier-Feature Inputs for Free-Breathing Cardiac MRI Reconstruction.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Implicit Neural Networks With Fourier-Feature Inputs for Free-Breathing Cardiac MRI Reconstruction

Reference 51

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Observation af49c944-00f9-49c8-9615-efd22e7ee12c · outbound

This paper cites Unsupervised reconstruction of accelerated cardiac cine MRI using neural fields.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unsupervised reconstruction of accelerated cardiac cine MRI using neural fields

Reference 52

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Observation e1a45c53-e173-4502-8599-c576c3ebae7a · outbound

This paper cites B1 inhomogeneity-corrected T1 mapping and quantitative magnetization transfer imaging via simultaneously estimating Bloch-Siegert shift and magnetization transfer effects.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement B1 inhomogeneity-corrected T1 mapping and quantitative magnetization transfer imaging via simultaneously estimating Bloch-Siegert shift and magnetization transfer effects

Reference 53

Resolution: verified exact; doi, observed 2026-08-06T13:48:43.731787Z

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Observation 3e13c914-4c56-4487-b237-b69abf83fa29 · outbound

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

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement 3D cine-magnetic resonance imaging using spatial and temporal implicit neural representation learning (STINR-MR)

Reference 54

Resolution: verified exact; doi, observed 2026-08-06T13:48:44.244744Z

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Observation 8a2b58c7-58eb-488b-89a8-1c4d2653041e · outbound

This paper cites Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery

Reference 55

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Observation d6dcac35-2664-44b9-acbe-17c4182bf3c1 · outbound

This paper cites Learned Proximal Networks for Quantitative Susceptibility Mapping.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Learned Proximal Networks for Quantitative Susceptibility Mapping

Reference 56

Resolution: verified exact; doi, observed 2026-08-06T13:48:43.483534Z

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Observation a1d25211-b265-49be-aa27-aa5d2bb3496f · outbound

This paper cites MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping

Reference 57

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Observation 934c0311-4d0b-4e0a-a720-d01d72dabd00 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 58

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Observation 119d215c-607b-4829-8ef0-37847099fb97 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement LoRA: Low-Rank Adaptation of Large Language Models

Reference 59

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Observation f561c435-da3a-42ec-b9d5-2ded8d6ccf38 · outbound

This paper cites Quantitative magnetization transfer imaging in postmortem multiple sclerosis brain.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Quantitative magnetization transfer imaging in postmortem multiple sclerosis brain

Reference 60

Resolution: verified exact; doi, observed 2026-08-06T13:48:43.154763Z

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Observation 8da2ed96-e348-4d13-8331-f7a5ae947b75 · outbound

This paper cites Proximal algorithms.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Proximal algorithms

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:48:56.342650Z

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Observation 67de1908-b4ba-4f98-bf05-a47b77803b8d · outbound

This paper cites Quantitative interpretation of magnetization transfer.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Quantitative interpretation of magnetization transfer

Reference 62

Resolution: verified exact; doi, observed 2026-08-06T13:48:42.423122Z

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Observation 84ac668b-c6ec-4b34-ba22-54d875591a89 · outbound

This paper cites Magnetization transfer effects on T1-weighted three-dimensional gradient-echo MR images of a phantom simulating enhancing brain lesions.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Magnetization transfer effects on T1-weighted three-dimensional gradient-echo MR images of a phantom simulating enhancing brain lesions

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:48:56.000801Z

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Observation 45959a87-3898-4a65-b88f-98140d249071 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Adam: A Method for Stochastic Optimization

Reference 64

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Observation 7e978ca4-a23f-4719-ae68-9b667d6125e6 · outbound

This paper cites ESPIRiT — An Eigenvalue Approach to Autocalibrating Parallel MRI: Where SENSE meets GRAPPA.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement ESPIRiT — An Eigenvalue Approach to Autocalibrating Parallel MRI: Where SENSE meets GRAPPA

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T13:48:41.276621Z

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Observation c851636e-3447-4210-97a8-25e7eb9df87f · outbound

This paper cites Statistical methods for assessing agreement between two methods of clinical measurement.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Statistical methods for assessing agreement between two methods of clinical measurement

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:48:55.679631Z

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Observation 93ee380f-f71c-4458-9a41-9b2d6ed50401 · outbound

This paper cites Multilayer feedforward networks are universal approximators.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Multilayer feedforward networks are universal approximators

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T13:48:41.596929Z

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Observation 9edba1e1-9221-4073-9eb7-de0989c5ca94 · outbound

This paper cites Magnetization transfer in cartilage and its constituent macromolecules.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Magnetization transfer in cartilage and its constituent macromolecules

Reference 68

Resolution: verified exact; doi, observed 2026-08-06T13:48:42.682262Z

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Observation c4f1f9fd-3c79-4f41-acef-b0252b82f60a · outbound

This paper cites Instant Neural Graphics Primitives with a Multiresolution Hash Encoding.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Instant Neural Graphics Primitives with a Multiresolution Hash Encoding

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-06T13:48:41.784749Z

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Observation 27e10e3b-d05c-4eaa-bfe7-27778676f4e3 · outbound

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Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 188

Resolution: verified exact; doi, observed 2026-08-06T13:48:46.663407Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2fbdd7ca-b857-4dad-b8e7-d33fb4907378 · outbound

This paper cites an unresolved cited work.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 588

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Observation 0a851a72-df9a-4b81-9381-577766eb59fc · outbound

This paper cites an unresolved cited work.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 1289

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T13:48:49.516471Z

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Observation 4abb109f-a18a-4055-b0c9-a6adb0574c9b · outbound

This paper cites an unresolved cited work.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 1811

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T13:48:53.181757Z

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Observation 2ed0420f-89aa-4661-806e-51875493c4ad · outbound

This paper cites an unresolved cited work.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 2156

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Observation 732f7552-4915-4c7f-ba7d-40060caa80bb · outbound

This paper cites an unresolved cited work.

Accelerating multiparametric quantitative MRI using self-supervised scan-specific implicit neural representation with model reinforcement Unresolved cited work

Reference 2309

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