Paper Citation Record · LEDGER

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction

As of 8 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2505.24136.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.24136 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:38:26.552845Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:38:24.000185Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T12:38:26.689161Z

Reference resolution

29 of 29 outbound references displayed

verified exact1
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unresolved3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ed415516-63a9-48c6-8375-b265137225e3 · outbound

This paper cites Physics-driven deep learning (PD-DL) models have emerged as a powerful solution to accelerate MRI while preserving im- age quality [1–5].

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Physics-driven deep learning (PD-DL) models have emerged as a powerful solution to accelerate MRI while preserving im- age quality [1–5]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:30.675319Z

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Observation 3917974c-9470-4152-9c7c-69f4ff81eaa3 · outbound

This paper cites Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:38:26.811814Z

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Observation fb120879-8ba7-4480-ab5a-c41352d4df81 · outbound

This paper cites Our key innovation involves augmenting the MM-SSDU loss, as defined in (4), with a novel consistency term, which we refer to as sparse parallel imaging consistency.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Our key innovation involves augmenting the MM-SSDU loss, as defined in (4), with a novel consistency term, which we refer to as sparse parallel imaging consistency

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:30.470544Z

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Observation 05828401-7534-4419-af1f-4dffb62b4778 · outbound

This paper cites Imaging Experiments and Implementation Details We conducted a comprehensive evaluation of our method with both qualitative and quantitative assessments.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Imaging Experiments and Implementation Details We conducted a comprehensive evaluation of our method with both qualitative and quantitative assessments

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:30.277133Z

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Observation 80dc605b-b7cd-4166-8594-dc3c863ad4f8 · outbound

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Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:38:30.173265Z

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Observation e6e221c6-41fd-433e-9aa5-6797b29e3bc9 · outbound

This paper cites an unresolved cited work.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Unresolved cited work

Reference 6

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Observation 91c0bbab-1cd0-4add-8b27-9d6c3a0cb3bc · outbound

This paper cites A deep cascade of convolutional neural networks for dynamic MR image reconstruction,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction A deep cascade of convolutional neural networks for dynamic MR image reconstruction,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:29.944299Z

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Observation fa57d0ef-71b3-4a8e-b43c-0face23b1c2d · outbound

This paper cites Learning a vari- ational network for reconstruction of accelerated MRI data,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Learning a vari- ational network for reconstruction of accelerated MRI data,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:29.819701Z

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Observation df80ad01-cd7c-462a-bfa1-aa2ef4d189e1 · outbound

This paper cites MoDL: Model-based deep learning architecture for inverse problems,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction MoDL: Model-based deep learning architecture for inverse problems,

Reference 9

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Source-reported events for the cited work

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Observation 4667053e-514b-43c5-9367-eca81be9dab5 · outbound

This paper cites Convolutional recurrent neural networks for dynamic MR image reconstruction,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Convolutional recurrent neural networks for dynamic MR image reconstruction,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:29.698671Z

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Observation 6eecbd58-18b2-4dfb-a64f-9987c4773052 · outbound

This paper cites ADMM-CSNet: A deep learning approach for image compressive sensing,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction ADMM-CSNet: A deep learning approach for image compressive sensing,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:29.568016Z

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Observation 13417d71-322c-4a64-9b01-ad7b18222864 · outbound

This paper cites Neural proximal gra- dient descent for compressive imaging,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Neural proximal gra- dient descent for compressive imaging,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:29.374635Z

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Observation 95612cf5-4568-4af8-9c14-54974ae01736 · outbound

This paper cites Multi-mask self-supervised learning for physics-guided neural networks in highly accelerated magnetic resonance imaging,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Multi-mask self-supervised learning for physics-guided neural networks in highly accelerated magnetic resonance imaging,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:29.265688Z

Source-reported events for the cited work

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Observation 053e09a7-bfb5-4d8a-be07-2e17b8ba66e5 · outbound

This paper cites Equivariant imaging: Learning beyond the range space,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Equivariant imaging: Learning beyond the range space,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:29.158966Z

Source-reported events for the cited work

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Observation 4fe96300-da22-4098-a1dc-9c76873249eb · outbound

This paper cites Robust compressed sensing MRI with deep generative priors,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Robust compressed sensing MRI with deep generative priors,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:29.069591Z

Source-reported events for the cited work

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Observation 2aed25ca-3e7a-44f8-b56d-412bacc48ea3 · outbound

This paper cites Score-based diffusion models for accelerated MRI,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Score-based diffusion models for accelerated MRI,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:28.989900Z

Source-reported events for the cited work

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Observation 2c9e21a6-c10a-4634-8abb-a3a72434cb65 · outbound

This paper cites Cycle- consistent self-supervised learning for improved highly- accelerated MRI reconstruction,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Cycle- consistent self-supervised learning for improved highly- accelerated MRI reconstruction,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:28.896923Z

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Observation a0a1316e-5641-44b2-baf1-c6967fb3c33e · outbound

This paper cites A theoretical framework for self-supervised MR image reconstruction using sub- sampling via variable density Noisier2Noise,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction A theoretical framework for self-supervised MR image reconstruction using sub- sampling via variable density Noisier2Noise,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:28.800697Z

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Observation caacf90c-31b4-49bb-aeed-2ef4636dab0c · outbound

This paper cites fastMRI: A publicly available raw k-space and DICOM dataset of knee im- ages for accelerated MR image reconstruction using ma- chine learning,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction fastMRI: A publicly available raw k-space and DICOM dataset of knee im- ages for accelerated MR image reconstruction using ma- chine learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:28.605135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7899f876-646b-4731-bfa7-200e1241a917 · outbound

This paper cites Unsuper- vised learning from incomplete measurements for in- verse problems,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Unsuper- vised learning from incomplete measurements for in- verse problems,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:28.385609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 58de776d-5917-4db8-81f6-0d8c6373f1f7 · outbound

This paper cites SENSE: Sensitivity encoding for fast MRI,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction SENSE: Sensitivity encoding for fast MRI,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:28.219820Z

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Observation 08238ebd-326c-44d2-9825-8499cfcb61e3 · outbound

This paper cites Advances in sensitivity encoding with arbitrary k-space trajectories,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Advances in sensitivity encoding with arbitrary k-space trajectories,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:28.059205Z

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Observation 3077a872-b5a8-4dee-85a8-a9cb450ef9ee · outbound

This paper cites Gen- eralized autocalibrating partially parallel acquisitions (GRAPPA),.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Gen- eralized autocalibrating partially parallel acquisitions (GRAPPA),

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:27.839359Z

Source-reported events for the cited work

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Observation acca750d-4b26-407d-91d9-2440e7703ac3 · outbound

This paper cites Optimization methods for magnetic res- onance image reconstruction,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Optimization methods for magnetic res- onance image reconstruction,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:27.651679Z

Source-reported events for the cited work

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Observation 7e82ba47-55f5-4bfc-9449-4de3d2ff0dc3 · outbound

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

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Sparse MRI: The application of compressed sensing for rapid MR imaging,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:27.546482Z

Source-reported events for the cited work

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Observation a1587e83-216f-4141-924b-d445b0f14041 · outbound

This paper cites Enhanc- ing sparsity by reweighted ℓ1 minimization,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Enhanc- ing sparsity by reweighted ℓ1 minimization,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:27.509486Z

Source-reported events for the cited work

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Observation 737ac247-9c9b-46d2-af5f-ad95daedd6dd · outbound

This paper cites Assessment of the gen- eralization of learned image reconstruction and the po- tential for transfer learning,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction Assessment of the gen- eralization of learned image reconstruction and the po- tential for transfer learning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:27.399076Z

Source-reported events for the cited work

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Observation 1f7dfc10-d73c-4bd5-ab74-ffc345179c2d · outbound

This paper cites NTIRE 2017 challenge on single im- age super-resolution: Methods and results,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction NTIRE 2017 challenge on single im- age super-resolution: Methods and results,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:27.231695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0451de78-242a-4e94-93c5-4dc9dc4bb2d4 · outbound

This paper cites The dual-tree complex wavelet transform,.

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction The dual-tree complex wavelet transform,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:38:27.030656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation 3917974c-9470-4152-9c7c-69f4ff81eaa3 · inbound