Paper Citation Record · LEDGER

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models

As of 22 July 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2605.01185.

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

pith.paper-citation-record.v1
2605.01185 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-09T15:26:52.844479Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-21T06:31:05.380196+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

33 of 33 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bbdd2241-a566-42dd-9e4a-a260820e8fae · outbound

This paper cites an unresolved cited work.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Unresolved cited work

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.283209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation edc08b6c-96b6-41ec-9f73-3ff29f360f0c · outbound

This paper cites Seeing what a gan cannot generate.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Seeing what a gan cannot generate

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.275789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 09377f0e-84c9-4965-beb4-3669567b74e5 · outbound

This paper cites Large scale GAN training for high fidelity natural image synthe- sis.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Large scale GAN training for high fidelity natural image synthe- sis

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.353777Z

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Observation e10ea1eb-8ff2-40c6-9f0b-bfffde29014b · outbound

This paper cites Score-based diffusion models for accelerated mri.Medical image analysis, 80: 102479.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Score-based diffusion models for accelerated mri.Medical image analysis, 80: 102479

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.345392Z

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No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation a7f9cbb6-2955-432a-91bf-0d84c6f00369 · outbound

This paper cites Solving 3d inverse problems using pre-trained 2d diffusion models.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Solving 3d inverse problems using pre-trained 2d diffusion models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.357849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 848b0f59-11db-4fcd-9f55-3fc42c180b81 · outbound

This paper cites Synthesizing complex- valued multicoil mri data from magnitude-only images.Bio- engineering, 10(3):358.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Synthesizing complex- valued multicoil mri data from magnitude-only images.Bio- engineering, 10(3):358

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.328839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation a4ac9367-8668-46e8-a465-15e1b983c374 · outbound

This paper cites Diffusion models beat gans on image synthesis.Advances in neural informa- tion processing systems, 34:8780–8794.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Diffusion models beat gans on image synthesis.Advances in neural informa- tion processing systems, 34:8780–8794

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.337155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 96016f1a-b78f-4f11-b84a-fd680f70fd23 · outbound

This paper cites Synthetic data accelerates the development of gener- alizable learning-based algorithms for x-ray image analysis.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Synthetic data accelerates the development of gener- alizable learning-based algorithms for x-ray image analysis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.370849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 482c749f-59d3-4f39-bce8-cc1ccea55a44 · outbound

This paper cites Generative adversarial networks.Commu- nications of the ACM, 63(11):139–144.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Generative adversarial networks.Commu- nications of the ACM, 63(11):139–144

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.366577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 185a624b-ede3-453b-af09-c2925afaa477 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.319780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation e75c12b7-1ad0-4451-899a-5937527d0213 · outbound

This paper cites Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.362292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 57dc46c3-a419-4c19-8a2a-dbe36a9f071f · outbound

This paper cites Image-to-image translation with conditional adver- sarial networks.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Image-to-image translation with conditional adver- sarial networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.388343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 2481d8e0-78e3-418b-97ef-b766fd22c567 · outbound

This paper cites Cola-diff: Conditional latent diffusion model for multi- modal mri synthesis.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Cola-diff: Conditional latent diffusion model for multi- modal mri synthesis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.315454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 5eeb37b9-3e7d-4fc1-994b-37940bb9dc09 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models A style-based generator architecture for generative adversarial networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.324553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 94a7c991-45fa-468e-97f8-494cc3f2310f · outbound

This paper cites Analyzing and improving the image quality of stylegan.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Analyzing and improving the image quality of stylegan

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.332727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 2f6bfb06-0e4f-4220-95cf-489e7c23def8 · outbound

This paper cites Kingma and Jimmy Ba.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Kingma and Jimmy Ba

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.341291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 4f79532b-c727-494f-b0b3-4b73ad408ba0 · outbound

This paper cites an unresolved cited work.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Unresolved cited work

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.349571Z

Source-reported events for the cited work

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Observation e3c87c3e-5cb9-42aa-b337-dd33a0276e97 · outbound

This paper cites an unresolved cited work.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Unresolved cited work

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.294994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 21d1e992-9168-45d7-812f-a62dfcd30a33 · outbound

This paper cites A multimodal comparison of latent denois- ing diffusion probabilistic models and generative adversarial networks for medical image synthesis.Scientific Reports, 13 (1):12098.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models A multimodal comparison of latent denois- ing diffusion probabilistic models and generative adversarial networks for medical image synthesis.Scientific Reports, 13 (1):12098

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.383878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 54381ba8-eb9c-4937-b4ee-51aa27646e25 · outbound

This paper cites Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:41:12.108390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation d8c72c0c-53de-460d-8197-f511ce7aa530 · outbound

This paper cites Da Costa.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Da Costa

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.298834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation ff586c47-01ef-4760-8ed9-a39fb20cd6fb · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models High-resolution image synthesis with latent diffusion models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.375372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 4e3f222d-a372-4b52-a656-ce54e167db17 · outbound

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

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models U- net: Convolutional networks for biomedical image segmen- tation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.379517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f1769783-1fbc-4f18-9af9-34ccedcc777d · outbound

This paper cites pytorch-fid: FID Score for PyTorch.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models pytorch-fid: FID Score for PyTorch

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.291195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation aabe0e15-7b0b-47cd-bf1d-58d6cf364406 · outbound

This paper cites Improved techniques for training score-based generative models.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Improved techniques for training score-based generative models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.303075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation cfc40bdb-2481-4bdf-8dca-d190ae4cf438 · outbound

This paper cites Kingma, Ab- hishek Kumar, Stefano Ermon, and Ben Poole.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Kingma, Ab- hishek Kumar, Stefano Ermon, and Ben Poole

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.307222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 260afda3-aa57-4090-b7f4-ed56d212ff1b · outbound

This paper cites an unresolved cited work.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Unresolved cited work

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.279479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation bab88bd2-5a4a-4a5a-ae15-51abf6963526 · outbound

This paper cites Simulating single-coil mri from the responses of multiple coils.Communications in Ap- plied Mathematics and Computational Science, 15(2):115– 127.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Simulating single-coil mri from the responses of multiple coils.Communications in Ap- plied Mathematics and Computational Science, 15(2):115– 127

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.272073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 3dfd97c9-4927-4b81-aa58-625055ebe3a9 · outbound

This paper cites Brain tumor segmentation using synthetic mr images-a comparison of gans and diffusion models.Sci- entific Data, 11(1):259.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Brain tumor segmentation using synthetic mr images-a comparison of gans and diffusion models.Sci- entific Data, 11(1):259

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.287385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f2f6e72c-79b7-496e-bdbc-b07987acd865 · outbound

This paper cites A connection between score matching and denoising autoencoders.Neural Computation, 23(7):1661– 1674.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models A connection between score matching and denoising autoencoders.Neural Computation, 23(7):1661– 1674

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.311370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 2ca5d809-8f1f-4459-9c81-459e0b428a3a · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:11:28.267689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation c050cf1c-e852-4642-93b0-530f844ccea0 · outbound

This paper cites One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:41:12.104339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 0e62122c-4be0-4627-9bf0-018b61a525ac · outbound

This paper cites fastMRI: An Open Dataset and Benchmarks for Accelerated MRI.

Phase-map synthesis from magnitude-only MR images using conditional score-based diffusion models with application in training of accelerated MRI reconstruction models fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-23T22:06:02.657571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

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