Paper Citation Record · LEDGER

Improving Medical Image Generative Models with Fr\'echet Distance Loss

As of 7 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2607.13300.

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

pith.paper-citation-record.v1
2607.13300 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:39:39.720270Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact3
verified fuzzy0
unresolved22
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b1d2bda4-4075-4b4f-b471-37a556544c7b · outbound

This paper cites Scientific Data4, 170117 (2017).https://doi.org/10.1038/sdata.2017.117.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Scientific Data4, 170117 (2017).https://doi.org/10.1038/sdata.2017.117

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:36.700842Z

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Unavailable: canonical work link unavailable.

Observation a3bae7da-bce6-40ae-abbb-4659ce06d69f · outbound

This paper cites Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:36.813780Z

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Observation cc6fa6b2-171a-4992-872b-313bd5bf7869 · outbound

This paper cites Medical Image Analysis84, 102680 (2023).https://doi.org/10.1016/j.media.2022.102680.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Medical Image Analysis84, 102680 (2023).https://doi.org/10.1016/j.media.2022.102680

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:36.921180Z

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Observation cc640965-6be2-4886-a406-a141ef36a8ae · outbound

This paper cites Demystifying MMD GANs.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Demystifying MMD GANs

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:37.053469Z

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Observation 4bc13743-90aa-4909-9c0d-068d9ba95f4a · outbound

This paper cites MONAI: An open-source framework for deep learning in healthcare.

Improving Medical Image Generative Models with Fr\'echet Distance Loss MONAI: An open-source framework for deep learning in healthcare

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:37.190350Z

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Observation 8cec395e-6102-4dad-ae28-e1744f0e7388 · outbound

This paper cites GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium.

Improving Medical Image Generative Models with Fr\'echet Distance Loss GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:37.341187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dbccc22-e90c-470d-9354-1e17d82d2274 · outbound

This paper cites In: Advances in Neural Information Processing Systems.

Improving Medical Image Generative Models with Fr\'echet Distance Loss In: Advances in Neural Information Processing Systems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:37.456830Z

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Observation 4286055d-eca6-4a79-9f38-d567bcd4b375 · outbound

This paper cites In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Improving Medical Image Generative Models with Fr\'echet Distance Loss In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:37.541028Z

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Unavailable: canonical work link unavailable.

Observation 88d36c5a-b2fc-4673-b77f-8daa870ec770 · outbound

This paper cites Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-02T05:43:30.771571Z

Source-reported events for the cited work

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

Observation 4d94e7de-a56b-4f59-bc1e-625602a837f1 · outbound

This paper cites Medical Image Analysis110, 103943 (2026).

Improving Medical Image Generative Models with Fr\'echet Distance Loss Medical Image Analysis110, 103943 (2026)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:37.766531Z

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Observation 7307dfaa-bcca-4b36-ba33-d1af5f9a864e · outbound

This paper cites an unresolved cited work.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:37.876191Z

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Observation 09911a04-22cf-4425-8047-2138fa23024a · outbound

This paper cites MedSegFactory: Text-Guided Generation of Medical Image-Mask Pairs.

Improving Medical Image Generative Models with Fr\'echet Distance Loss MedSegFactory: Text-Guided Generation of Medical Image-Mask Pairs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:38.024136Z

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Unavailable: canonical work link unavailable.

Observation fac36a8d-646d-43bc-be02-85763f5d0efa · outbound

This paper cites Backpropagating through Fr\'echet Inception Distance.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Backpropagating through Fr\'echet Inception Distance

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:38.147516Z

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Observation 8eef0a86-2cfe-4047-af4c-3664b7615045 · outbound

This paper cites Radiology: Artificial Intelligence4(5), e210315 (2022).https://doi.org/10.1148/ryai.210315.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Radiology: Artificial Intelligence4(5), e210315 (2022).https://doi.org/10.1148/ryai.210315

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:38.261355Z

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Observation c511c9f5-5b12-446a-81a8-7bf79b38ed41 · outbound

This paper cites IEEE transactions on medical imaging34(10), 1993–2024 (2015).https://doi.org/10.1109/TMI.2014.2377694.

Improving Medical Image Generative Models with Fr\'echet Distance Loss IEEE transactions on medical imaging34(10), 1993–2024 (2015).https://doi.org/10.1109/TMI.2014.2377694

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:38.375409Z

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Unavailable: canonical work link unavailable.

Observation 548c54ff-386f-43b7-9fee-6c1016f9d9fc · outbound

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

Improving Medical Image Generative Models with Fr\'echet Distance Loss U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:38.509790Z

Source-reported events for the cited work

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Observation 37ab3ff8-ace4-4c26-80e1-c43ed70e4bf7 · outbound

This paper cites Improved Techniques for Training GANs.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Improved Techniques for Training GANs

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:38.679515Z

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Observation 68f993c5-1eb2-48e8-ad4e-f76b27de7d8a · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Progressive Distillation for Fast Sampling of Diffusion Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:38.798683Z

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Observation 4e5f0d50-313d-4d13-a32b-8de9085dee0f · outbound

This paper cites MM-DINOv2: Adapting Foundation Models for Multi-Modal Medical Image Analysis.

Improving Medical Image Generative Models with Fr\'echet Distance Loss MM-DINOv2: Adapting Foundation Models for Multi-Modal Medical Image Analysis

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-02T05:43:30.430250Z

Source-reported events for the cited work

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

Observation 2e044372-c3db-4160-ab41-1a7ecf268ecf · outbound

This paper cites Denoising Diffusion Implicit Models.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Denoising Diffusion Implicit Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:39.028358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2046a8fa-f66d-4426-8db4-d6b1b5d99f2b · outbound

This paper cites In: 2016 IEEE Conference on Com- puter Vision and Pattern Recognition (CVPR).

Improving Medical Image Generative Models with Fr\'echet Distance Loss In: 2016 IEEE Conference on Com- puter Vision and Pattern Recognition (CVPR)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:39.182083Z

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Unavailable: canonical work link unavailable.

Observation 9a0a469c-3f76-4187-8529-2c9ea29f722e · outbound

This paper cites In: Medical Image Computing and Computer Assisted Intervention – MICCAI.

Improving Medical Image Generative Models with Fr\'echet Distance Loss In: Medical Image Computing and Computer Assisted Intervention – MICCAI

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:39.301804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7884bb62-47b6-400e-b574-aa1399054513 · outbound

This paper cites Sci- entific Data13(1), 31 (2025).https://doi.org/10.1038/s41597-025-06343-4.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Sci- entific Data13(1), 31 (2025).https://doi.org/10.1038/s41597-025-06343-4

Reference 23

Resolution: verified exact; doi, observed 2026-08-02T05:43:30.087138Z

Source-reported events for the cited work

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

Observation 7ed2e3b0-4bb0-4ee8-9d91-a654fee8388e · outbound

This paper cites Representation Fr\'echet Loss for Visual Generation.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Representation Fr\'echet Loss for Visual Generation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:39.550199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f47cc588-a652-4e63-b1c6-2d7c024e31f5 · outbound

This paper cites Nature Communications16(1), 6486 (2025).https://doi.org/10.1038/ s41467-025-61754-6 Improving Medical Image Generative Models with Fréchet Distance Loss 11.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Nature Communications16(1), 6486 (2025).https://doi.org/10.1038/ s41467-025-61754-6 Improving Medical Image Generative Models with Fréchet Distance Loss 11

Reference 25

Resolution: malformed identifier; no resolver link, observed 2026-08-02T05:39:39.648696Z

Source-reported events for the cited work

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Observation 635dc67d-2f70-4921-a0cf-838b2e084678 · outbound

This paper cites BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs.

Improving Medical Image Generative Models with Fr\'echet Distance Loss BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T05:39:39.720270Z

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Observation d2db813c-c532-4986-bd99-ee6554d07ba6 · outbound

This paper cites an unresolved cited work.

Improving Medical Image Generative Models with Fr\'echet Distance Loss Unresolved cited work

Reference 2024

Resolution: malformed identifier; no resolver link, observed 2026-08-02T05:39:39.399304Z

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Pith citing papers

No inbound Pith citation observations are available.