Robust multi-coil MRI reconstruction via self-supervised denoising | Paper Citation Record

Observation 4144c9b6-bd84-4dfe-bc00-58ac69760a6b · outbound

This paper cites Motion artifacts in MRI: A complex problem with many partial solutions.Journal of Magnetic Resonance Imaging42.(4) (2015), 887–901.

Robust multi-coil MRI reconstruction via self-supervised denoising Motion artifacts in MRI: A complex problem with many partial solutions.Journal of Magnetic Resonance Imaging42.(4) (2015), 887–901

Reference 1

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This paper cites A., and Seiberlich, N.

Robust multi-coil MRI reconstruction via self-supervised denoising A., and Seiberlich, N

Reference 2

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Robust multi-coil MRI reconstruction via self-supervised denoising Unresolved cited work

Reference 3

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This paper cites N., Fleysher, R., and Lipton, M.

Robust multi-coil MRI reconstruction via self-supervised denoising N., Fleysher, R., and Lipton, M

Reference 4

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Robust multi-coil MRI reconstruction via self-supervised denoising Unresolved cited work

Reference 5

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This paper cites and Rathi, Y.

Robust multi-coil MRI reconstruction via self-supervised denoising and Rathi, Y

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Observation 2699240d-62ee-4436-8aec-08fa06ac2a6b · outbound

This paper cites Deep learning for ac- celerated and robust MRI reconstruction.Magnetic Resonance Materials in Physics, Biology and Medicine(2024), 1–34.

Robust multi-coil MRI reconstruction via self-supervised denoising Deep learning for ac- celerated and robust MRI reconstruction.Magnetic Resonance Materials in Physics, Biology and Medicine(2024), 1–34

Reference 7

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Observation 56391751-9f93-4b51-9eed-35bc013a0f3d · outbound

This paper cites P., Weiger, M., Scheidegger, M.

Robust multi-coil MRI reconstruction via self-supervised denoising P., Weiger, M., Scheidegger, M

Reference 8

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This paper cites A., Jakob, P.

Robust multi-coil MRI reconstruction via self-supervised denoising A., Jakob, P

Reference 9

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This paper cites J., et al.

Robust multi-coil MRI reconstruction via self-supervised denoising J., et al

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This paper cites Accelerating magnetic resonance imaging via deep learning.

Robust multi-coil MRI reconstruction via self-supervised denoising Accelerating magnetic resonance imaging via deep learning

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This paper cites Learning a variational network for reconstruc- tion of accelerated MRI data.Magnetic resonance in medicine79.(6) (2018), 3055–3071.

Robust multi-coil MRI reconstruction via self-supervised denoising Learning a variational network for reconstruc- tion of accelerated MRI data.Magnetic resonance in medicine79.(6) (2018), 3055–3071

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Observation ea9e447c-7766-467b-b6a1-e473cac2e421 · outbound

This paper cites N., Hajnal, J.

Robust multi-coil MRI reconstruction via self-supervised denoising N., Hajnal, J

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This paper cites K., Mani, M.

Robust multi-coil MRI reconstruction via self-supervised denoising K., Mani, M

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This paper cites S., and Cao, P.

Robust multi-coil MRI reconstruction via self-supervised denoising S., and Cao, P

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This paper cites C., Baumgartner, C.

Robust multi-coil MRI reconstruction via self-supervised denoising C., Baumgartner, C

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This paper cites G., and Tamir, J.

Robust multi-coil MRI reconstruction via self-supervised denoising G., and Tamir, J

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Observation c4c70fe8-295d-47d8-98b8-f81800ee6466 · outbound

This paper cites and Ye, J.

Robust multi-coil MRI reconstruction via self-supervised denoising and Ye, J

Reference 18

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Observation fdc551b5-e625-49ef-bbeb-588ab3c869b5 · outbound

This paper cites Bayesian MRI reconstruction with joint uncertainty estimation using diffusion models.Magnetic Resonance in Medicine(2023).

Robust multi-coil MRI reconstruction via self-supervised denoising Bayesian MRI reconstruction with joint uncertainty estimation using diffusion models.Magnetic Resonance in Medicine(2023)

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This paper cites A survey of emerging applications of diffusion probabilistic models in mri.Meta-Radiology (2024), 100082.

Robust multi-coil MRI reconstruction via self-supervised denoising A survey of emerging applications of diffusion probabilistic models in mri.Meta-Radiology (2024), 100082

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This paper cites Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data.

Robust multi-coil MRI reconstruction via self-supervised denoising Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data

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This paper cites Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction.

Robust multi-coil MRI reconstruction via self-supervised denoising Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction

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This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Robust multi-coil MRI reconstruction via self-supervised denoising Score-Based Generative Modeling through Stochastic Differential Equations

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Observation a9da5f0b-e264-46d0-b6d4-5fc907f6b859 · outbound

This paper cites and Ermon, S.

Robust multi-coil MRI reconstruction via self-supervised denoising and Ermon, S

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Observation 7436a18b-ac7a-4640-b7c7-1a32d8b213df · outbound

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Robust multi-coil MRI reconstruction via self-supervised denoising Denoising diffusion probabilistic models.Advances in Neural Information Processing Systems33 (2020), 6840–6851

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.610056Z

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Observation 7e5b7c9e-1998-4ab6-bf88-d77a21ac668d · outbound

This paper cites Elucidating the design space of diffusion-based generativemodels.

Robust multi-coil MRI reconstruction via self-supervised denoising Elucidating the design space of diffusion-based generativemodels

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This paper cites R., Rickers, C., Kwong, R.

Robust multi-coil MRI reconstruction via self-supervised denoising R., Rickers, C., Kwong, R

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This paper cites A., Collins, J.

Robust multi-coil MRI reconstruction via self-supervised denoising A., Collins, J

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This paper cites Self- supervised learning of inverse problem solvers in medical imaging.

Robust multi-coil MRI reconstruction via self-supervised denoising Self- supervised learning of inverse problem solvers in medical imaging

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Robust multi-coil MRI reconstruction via self-supervised denoising Unresolved cited work

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Robust multi-coil MRI reconstruction via self-supervised denoising Self- supervised physics-based deep learning MRI reconstruction without fully-sampled data

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This paper cites and Chiew, M.

Robust multi-coil MRI reconstruction via self-supervised denoising and Chiew, M

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Robust multi-coil MRI reconstruction via self-supervised denoising E., et al

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Robust multi-coil MRI reconstruction via self-supervised denoising SPICER: Self-supervised learning for MRI with automatic coil sensitivity estimation and reconstruction.Magnetic Resonance in Medicine92.(3) (2024), 1048–1063

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This paper cites Ambient diffusion: Learning clean distributions from corrupted data.Advances in Neural Information Processing Systems 36 (2024).

Robust multi-coil MRI reconstruction via self-supervised denoising Ambient diffusion: Learning clean distributions from corrupted data.Advances in Neural Information Processing Systems 36 (2024)

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This paper cites Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data.

Robust multi-coil MRI reconstruction via self-supervised denoising Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data

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This paper cites C., Bhutto, D., and Rosen, M.

Robust multi-coil MRI reconstruction via self-supervised denoising C., Bhutto, D., and Rosen, M

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Robust multi-coil MRI reconstruction via self-supervised denoising hidden noise

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This paper cites Accelerating Low-field MRI: Compressed Sensing and AI for fast noise-robust imaging.arXiv preprint arXiv:2411.06704(2024).

Robust multi-coil MRI reconstruction via self-supervised denoising Accelerating Low-field MRI: Compressed Sensing and AI for fast noise-robust imaging.arXiv preprint arXiv:2411.06704(2024)

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This paper cites From Stein’s unbiased risk estimates to the method of generalized cross validation.

Robust multi-coil MRI reconstruction via self-supervised denoising From Stein’s unbiased risk estimates to the method of generalized cross validation

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Robust multi-coil MRI reconstruction via self-supervised denoising Monte-Carlo SURE: A black-box optimization of regular- ization parameters for general denoising algorithms.IEEE Transactions on image processing 17.(9) (2008), 1540–1554

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Robust multi-coil MRI reconstruction via self-supervised denoising and Chun, S

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Robust multi-coil MRI reconstruction via self-supervised denoising Unsupervised Learning with Stein's Unbiased Risk Estimator

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Robust multi-coil MRI reconstruction via self-supervised denoising Noise2self: Blind denoising by self-supervision

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Observation 381478cc-184d-498f-8525-dd47638a7dcc · outbound

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Robust multi-coil MRI reconstruction via self-supervised denoising Noise2void-learning denoising from single noisy im- ages

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Robust multi-coil MRI reconstruction via self-supervised denoising Noisier2noise: Learning to denoise from unpaired noisy data

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This paper cites and Ye, J.

Robust multi-coil MRI reconstruction via self-supervised denoising and Ye, J

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Robust multi-coil MRI reconstruction via self-supervised denoising DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models

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This paper cites Image Denoising: The Deep Learning Revolution and Beyond -- A Survey Paper --.

Robust multi-coil MRI reconstruction via self-supervised denoising Image Denoising: The Deep Learning Revolution and Beyond -- A Survey Paper --

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Observation 9c299d1f-0f4e-4eb1-8847-9a5ad685a6ce · outbound

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Robust multi-coil MRI reconstruction via self-supervised denoising Zero-shot noise2noise: Efficient image denoising without any data

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Observation d6412fe1-7a2f-4dd7-8566-7b4c49dcb161 · outbound

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Robust multi-coil MRI reconstruction via self-supervised denoising Self-supervised MRI denoising: leveraging Stein’s unbiased risk estimator and spatially resolved noise maps.Scientific Reports 13.(1) (2023)

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Observation b69597fa-6c3c-47ff-9cb8-093fb2d95508 · outbound

This paper cites Unsupervised Deep Basis Pursuit: Learning inverse problems without ground-truth data.

Robust multi-coil MRI reconstruction via self-supervised denoising Unsupervised Deep Basis Pursuit: Learning inverse problems without ground-truth data

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Observation 45fadb24-32a7-4c09-a4a1-f260fa4a7f24 · outbound

This paper cites K., Pramanik, A., John, M., and Jacob, M.

Robust multi-coil MRI reconstruction via self-supervised denoising K., Pramanik, A., John, M., and Jacob, M

Reference 53

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Observation bcd7498b-f30d-41b6-a42a-776bf5944e6d · outbound

This paper cites and Chiew, M.

Robust multi-coil MRI reconstruction via self-supervised denoising and Chiew, M

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.342439Z

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Observation 6aa49a86-f801-4b45-b930-7f425b60efde · outbound

This paper cites D., Ozturkler, B.

Robust multi-coil MRI reconstruction via self-supervised denoising D., Ozturkler, B

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.329436Z

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Observation b8c2d361-c1df-4b84-91e9-42b5009f46f3 · outbound

This paper cites Solving inverse problems with score- based generative priors learned from noisy data.

Robust multi-coil MRI reconstruction via self-supervised denoising Solving inverse problems with score- based generative priors learned from noisy data

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.312944Z

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Observation 190eed2e-bd4a-424e-b8fa-a121785b823b · outbound

This paper cites GSURE Denoising enables training of higher quality generative priors for accelerated Multi-Coil MRI Reconstruction.

Robust multi-coil MRI reconstruction via self-supervised denoising GSURE Denoising enables training of higher quality generative priors for accelerated Multi-Coil MRI Reconstruction

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.300654Z

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Observation 307ad02c-af03-483a-8965-87b58e5ae081 · outbound

This paper cites an unresolved cited work.

Robust multi-coil MRI reconstruction via self-supervised denoising Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:10:59.288427Z

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Observation a473e0f4-6df7-43c3-a850-bcd49635e4a1 · outbound

This paper cites fastMRI: A publicly available raw k-space and DI- COM dataset of knee images for accelerated MR image reconstruction using machine learning.

Robust multi-coil MRI reconstruction via self-supervised denoising fastMRI: A publicly available raw k-space and DI- COM dataset of knee images for accelerated MR image reconstruction using machine learning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.277169Z

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Observation 40f07751-ce1a-48dc-b768-8b301425038b · outbound

This paper cites T., Klasky, M.

Robust multi-coil MRI reconstruction via self-supervised denoising T., Klasky, M

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.267172Z

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Observation 2f9a66bf-8d5b-4d2e-9db0-7effd61870ce · outbound

This paper cites Course notes from “Statistical Machine Learning(2015), 1–12.

Robust multi-coil MRI reconstruction via self-supervised denoising Course notes from “Statistical Machine Learning(2015), 1–12

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.256740Z

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Observation ce6e2f20-ce39-4de4-87b2-bbf1f196b552 · outbound

This paper cites Unsupervised Learning to Solve Inverse Problems: Application to Single-Pixel Imaging.Colloque Francophone de Traitement du Signal et des Images (2022).

Robust multi-coil MRI reconstruction via self-supervised denoising Unsupervised Learning to Solve Inverse Problems: Application to Single-Pixel Imaging.Colloque Francophone de Traitement du Signal et des Images (2022)

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.246477Z

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Observation 8603e247-a541-4686-a9ee-03b996de0132 · outbound

This paper cites Solving Inverse Problems in Medical Imaging with Score-Based Generative Models.

Robust multi-coil MRI reconstruction via self-supervised denoising Solving Inverse Problems in Medical Imaging with Score-Based Generative Models

Reference 63

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Observation fcf3aec4-5656-4e95-ab95-ee5e39f88bfd · outbound

This paper cites Denoising Diffusion Restoration Models.Ad- vances in Neural Information Processing Systems(2022).

Robust multi-coil MRI reconstruction via self-supervised denoising Denoising Diffusion Restoration Models.Ad- vances in Neural Information Processing Systems(2022)

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.235930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4cbcfbb3-9b0d-40cd-8522-38d0b72b3ef7 · outbound

This paper cites an unresolved cited work.

Robust multi-coil MRI reconstruction via self-supervised denoising Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:10:59.223932Z

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Observation 64b409f7-05c7-4aa3-beaf-314f880beb1f · outbound

This paper cites Score-Based Diffusion Models as Principled Priors for Inverse Imaging.

Robust multi-coil MRI reconstruction via self-supervised denoising Score-Based Diffusion Models as Principled Priors for Inverse Imaging

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T17:10:58.644381Z

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This paper cites Diffusion models as plug-and-play priors.

Robust multi-coil MRI reconstruction via self-supervised denoising Diffusion models as plug-and-play priors

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.213303Z

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Observation 048150c8-0280-41d0-be3b-1ee9edc175ae · outbound

This paper cites A., Baraniuk, R.

Robust multi-coil MRI reconstruction via self-supervised denoising A., Baraniuk, R

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.203296Z

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Observation 24cb71c1-f8d3-4265-b373-417e82d9cfd0 · outbound

This paper cites and McVeigh, E.

Robust multi-coil MRI reconstruction via self-supervised denoising and McVeigh, E

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.190839Z

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Observation 2813ec7f-2a84-481d-8ee3-7d86fc811f51 · outbound

This paper cites I., et al.

Robust multi-coil MRI reconstruction via self-supervised denoising I., et al

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.178817Z

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Observation e0bbb07f-a0f5-4000-9934-0dd7758e672b · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Robust multi-coil MRI reconstruction via self-supervised denoising U-net: Convolutional networks for biomedical image segmentation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.166604Z

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Observation c08bc31f-d298-41fd-8277-399fc4466a97 · outbound

This paper cites Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning.

Robust multi-coil MRI reconstruction via self-supervised denoising Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T17:10:58.667770Z

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Unavailable: canonical work link unavailable.

Observation 1bd80727-fe30-456a-9311-eb2f100eadaf · outbound

This paper cites Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data.

Robust multi-coil MRI reconstruction via self-supervised denoising Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-12T17:10:58.671133Z

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Unavailable: canonical work link unavailable.

Observation fad42cf2-20cb-4e27-92cc-96b3f857c30c · outbound

This paper cites Stochastic Deep Restoration Priors for Imaging Inverse Problems.

Robust multi-coil MRI reconstruction via self-supervised denoising Stochastic Deep Restoration Priors for Imaging Inverse Problems

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-12T17:10:58.674329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a78af8c4-89b0-4c5f-8db2-af86b5286abf · outbound

This paper cites and Luisier, F.

Robust multi-coil MRI reconstruction via self-supervised denoising and Luisier, F

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.154960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 695cbc16-713e-4d24-9878-8955d4c93bb0 · outbound

This paper cites Noise2Noise: Learning Image Restoration without Clean Data.

Robust multi-coil MRI reconstruction via self-supervised denoising Noise2Noise: Learning Image Restoration without Clean Data

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:10:59.144229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 81fc2d12-5915-4d86-b919-53895157e1c3 · outbound

This paper cites UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate.

Robust multi-coil MRI reconstruction via self-supervised denoising UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-12T17:10:58.683739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05de258f-b531-4230-ad1c-5b7f8b74feff · outbound

This paper cites M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research.Scientific Data 10.(1) (2023), 264.

Robust multi-coil MRI reconstruction via self-supervised denoising M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research.Scientific Data 10.(1) (2023), 264

Reference 78

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T17:10:59.133395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 66772c40-a70f-41a4-9e82-4b933ed1a57a · outbound

This paper cites Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy.

Robust multi-coil MRI reconstruction via self-supervised denoising Imaging transformer for MRI denoising with the SNR unit training: enabling generalization across field-strengths, imaging contrasts, and anatomy

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-12T17:10:58.690017Z

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