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Paper Citation Record · LEDGER

Learning Segmentation from Radiology Reports

As of 24 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2507.05582.

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

pith.paper-citation-record.v1
2507.05582 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:30:55.541260Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7a5cc990-fbc1-4494-8801-0b29c8ac5715 · outbound

This paper cites arXiv preprint arXiv:2106.05735 (2021).

Learning Segmentation from Radiology Reports arXiv preprint arXiv:2106.05735 (2021)

Reference 1

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Observation 86a6a5ae-fd12-4f98-8b9d-3a16ddba3695 · outbound

This paper cites an unresolved cited work.

Learning Segmentation from Radiology Reports Unresolved cited work

Reference 2

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation eabb055f-d22c-43db-98c7-c862e9428f62 · outbound

This paper cites RadGPT: Constructing 3D Image-Text Tumor Datasets.

Learning Segmentation from Radiology Reports RadGPT: Constructing 3D Image-Text Tumor Datasets

Reference 3

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source=pdf_text observed=2026-08-06T19:30:53.244595Z digest=sha256:923d603978c841774c53d847b1284ce5e815ad2adde299ca5c65ec935e76bc79

Observation 952c2378-b383-4b63-8874-85675c411afc · outbound

This paper cites The Liver Tumor Segmentation Benchmark (LiTS).

Learning Segmentation from Radiology Reports The Liver Tumor Segmentation Benchmark (LiTS)

Reference 4

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source=pdf_text observed=2026-08-06T19:30:53.355156Z digest=sha256:51ad003a3b8d9f79288d2dd7b1c364fd2555bc2b841ab4d405eabddfb69c68c8

Observation 029f7139-d7a6-4758-b2c5-673fc216858e · outbound

This paper cites Research Square pp.

Learning Segmentation from Radiology Reports Research Square pp

Reference 5

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source=pdf_text observed=2026-08-06T19:30:53.412499Z digest=sha256:d9af02b02a24b79ae99507a603437482fab531d1c48ee62b262cf63c1cfb9a76

Observation 8342a8e4-4654-4fd2-a463-db47d9043cb7 · outbound

This paper cites Radiology: Artificial Intelligence 5(5), e230031 (2023).

Learning Segmentation from Radiology Reports Radiology: Artificial Intelligence 5(5), e230031 (2023)

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:53.482171Z digest=sha256:89ca97c82094d75be15b72c3b3d9c0b5ecc143897e1dc52e1f4aee7a574853e4

Observation 5aff2a71-c5bd-4912-94b9-b12125f7fd43 · outbound

This paper cites In: 2019 IEEE 16th In- ternational Symposium on Biomedical Imaging (ISBI 2019).

Learning Segmentation from Radiology Reports In: 2019 IEEE 16th In- ternational Symposium on Biomedical Imaging (ISBI 2019)

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:53.545500Z digest=sha256:ec4ff504b0ac33b3dab8cf1dd8d2c53224e3153b8ad6d81da04091b57c316d2d

Observation 1735aff6-7fa8-407f-9d41-be9860f83ed7 · outbound

This paper cites Machine Intelligence Research pp.

Learning Segmentation from Radiology Reports Machine Intelligence Research pp

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:53.621449Z digest=sha256:0d13f2251826c9f4da5e5fe1e336c0e2bde02f6ed14ea869f1951fe23af64367

Observation 60991db1-a993-449e-a46f-9a13a3d2eb9d · outbound

This paper cites an unresolved cited work.

Learning Segmentation from Radiology Reports Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:53.701051Z digest=sha256:f89515eae63cdb3ca15c7d4aba307b4bad4f7755fc2330287623011456e28eba

Observation 94060bce-1f4e-4cea-b7eb-ba6f011c4d0c · outbound

This paper cites The Llama 3 Herd of Models.

Learning Segmentation from Radiology Reports The Llama 3 Herd of Models

Reference 10

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source=pdf_text observed=2026-08-06T19:30:53.783953Z digest=sha256:f8a1947ecb2b313022e1e42b73804d5d18e6545b7d5827af794db64883524bc4

Observation 4d674fce-1018-4224-b1f3-f4ccbf0c3bff · outbound

This paper cites A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark.

Learning Segmentation from Radiology Reports A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark

Reference 11

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source=pdf_text observed=2026-08-06T19:30:53.884007Z digest=sha256:1f0d00470cdaaafa61ab7b7d8f709244ac8666dc163476661b02c6fd8586a790

Observation cd2639ba-7567-43a9-9d19-33c8c3de308b · outbound

This paper cites CT2Rep: Automated Radiology Report Generation for 3D Medical Imaging.

Learning Segmentation from Radiology Reports CT2Rep: Automated Radiology Report Generation for 3D Medical Imaging

Reference 12

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Observation 2c618fd0-7eb1-40a7-a141-ad40f79f972e · outbound

This paper cites The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes.

Learning Segmentation from Radiology Reports The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

Reference 13

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Observation c173efed-7514-4aeb-a474-1fc410161856 · outbound

This paper cites Nature Methods18(2), 203–211 (2021).

Learning Segmentation from Radiology Reports Nature Methods18(2), 203–211 (2021)

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 95136065-cb32-4251-b15d-bf13a8276901 · outbound

This paper cites nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation.

Learning Segmentation from Radiology Reports nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation

Reference 15

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source=pdf_text observed=2026-08-06T19:30:54.217818Z digest=sha256:ed2d78234bf3294175bc53306c88d8635dfa8a8cbffc4057090e993cbd7dffc1

Observation 5551990e-e0e3-4e2c-8f66-257d689bd30d · outbound

This paper cites Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines.

Learning Segmentation from Radiology Reports Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines

Reference 16

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source=pdf_text observed=2026-08-06T19:30:54.314031Z digest=sha256:e152b12ce38cbeea5c8627c0ee1a76e88fd83aefa98418a1dec54fe1662cd744

Observation 7f3d2885-dc90-4893-9224-0fade570ce7b · outbound

This paper cites AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation.

Learning Segmentation from Radiology Reports AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation

Reference 17

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source=pdf_text observed=2026-08-06T19:30:54.414392Z digest=sha256:6770932e10b3bb181f5f5f8b4ee865d0bd9db23d04d3a7b5c236c41870fff703

Observation a2eb7007-aa29-4b53-aa5b-df5f345b2a79 · outbound

This paper cites arXiv preprint arXiv:2501.03410 (2025),https://github.

Learning Segmentation from Radiology Reports arXiv preprint arXiv:2501.03410 (2025),https://github

Reference 18

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Observation 8d3099e0-142d-4b7f-95e6-825b8a9b0b52 · outbound

This paper cites Medical Image Analysis p.

Learning Segmentation from Radiology Reports Medical Image Analysis p

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 3eb591b0-690f-45b5-8d94-5a9adb9d8294 · outbound

This paper cites an unresolved cited work.

Learning Segmentation from Radiology Reports Unresolved cited work

Reference 20

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:54.722508Z digest=sha256:9dd68ee3fd394d50eebef484b0076f5fd22c789daea7be14771908e4db1921c5

Observation 9d352f20-ed82-4e7b-92a6-a2d5fbab5182 · outbound

This paper cites PanTS: The Pancreatic Tumor Segmentation Dataset.

Learning Segmentation from Radiology Reports PanTS: The Pancreatic Tumor Segmentation Dataset

Reference 21

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:54.810202Z digest=sha256:df622a7643f4fe1d190ccc48a77bff402674bf2ee81897f86970236591f5b89f

Observation da1ffc04-64e0-49fe-b301-d2dc1dfbc7c0 · outbound

This paper cites Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challenge.

Learning Segmentation from Radiology Reports Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challenge

Reference 22

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source=pdf_text observed=2026-08-06T19:30:54.881965Z digest=sha256:01ebd82e11161911d0d8cf535c60f1f01159e7a11d0b1c4cf3490b9b62d2c60e

Observation 86f72d95-2379-46c5-8ef3-154469cfb4be · outbound

This paper cites Cancer47(1), 207–214 (1981).

Learning Segmentation from Radiology Reports Cancer47(1), 207–214 (1981)

Reference 23

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 055175c5-8cb3-40a3-a4ef-39b3b84f53cf · outbound

This paper cites Diagnostic and interventional imaging101(1), 35–44 (2020).

Learning Segmentation from Radiology Reports Diagnostic and interventional imaging101(1), 35–44 (2020)

Reference 24

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:55.069865Z digest=sha256:ec41566a2f7ebd14c444b2808479b23f9ed829b3742bc330301d1d5b6b7f5a05

Observation a899f7c4-3684-4067-815b-c0adb8a527b0 · outbound

This paper cites In: Conference on Neural Information Processing Systems.

Learning Segmentation from Radiology Reports In: Conference on Neural Information Processing Systems

Reference 25

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:55.146593Z digest=sha256:cd35e0cbb9169112ee61af8381b3640b05321026ac6acf75f8e1314297e0a803

Observation 939fce21-5748-4001-a231-1f218881cbf3 · outbound

This paper cites Radiology: Artificial Intelligence 5(5) (2023).

Learning Segmentation from Radiology Reports Radiology: Artificial Intelligence 5(5) (2023)

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:30:55.223055Z digest=sha256:80da88a63e58ac5c4bdc671cf17ce1f6a4c55567eb3c1cb258601adb4f1c3be2

Observation 28ba0b0c-4757-467b-b882-022cfc0bbdce · outbound

This paper cites medRxiv (2022).

Learning Segmentation from Radiology Reports medRxiv (2022)

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:55.311572Z digest=sha256:f95a1e9579b5bcdb30be46689cb8ff9e324b6f0b942c65fe82da6b0af076df7b

Observation 6450b367-f0ac-45c4-937b-3cf1cff9b144 · outbound

This paper cites IEEE transactions on medical imaging40(6), 1618–1631 (2021).

Learning Segmentation from Radiology Reports IEEE transactions on medical imaging40(6), 1618–1631 (2021)

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:55.386214Z digest=sha256:dcbf639b4a226696f0e8f59594696c31f2222a042685d6c8b09001fbfffaa479

Observation ecdc2ff4-49c9-4b0d-9b52-7028ae25c82c · outbound

This paper cites an unresolved cited work.

Learning Segmentation from Radiology Reports Unresolved cited work

Reference 29

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T19:30:55.485416Z digest=sha256:641057e64637eecd68540798bc8ae3d5ec46a0e64aba8e7f0aa808cc615e3c57

Observation a44e972f-6af3-4fc8-9c9b-2757d14f6941 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention.

Learning Segmentation from Radiology Reports In: International Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 30

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Pith citing papers

No inbound Pith citation observations are available.