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Paper Citation Record · LEDGER

Learning Segmentation from Radiology Reports

As of 23 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 2026-08-22T06:32:14.747728+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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Unavailable: canonical work link unavailable.

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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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:53.482171Z digest=sha256:51445dabfd7a9e5ff7ca8fddb818a8881bdbe0ba862701ea827cbb8c16d45d08

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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raw_fallback, observed 2026-08-06T19:30:58.249566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:53.545500Z digest=sha256:f2c63409319865afa4834e079f811a69b3f188c854f00c13392f3e9a0cc3eb7b

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 2026-08-22T06:32:14.747728+00:00.

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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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:53.701051Z digest=sha256:a909a824a3500a1b1bc7383306357c6fdd9a279c6ef3fa698d586d50c759be66

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-reported events for the cited work

Unavailable: canonical work link unavailable.

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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source=pdf_text observed=2026-08-06T19:30:54.057497Z digest=sha256:daa7d8b354857d84616eb04183d57257abfd2fda6dc6603cc57546e86f3c370b

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 2026-08-22T06:32:14.747728+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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Unavailable: canonical work link unavailable.

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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source=pdf_text observed=2026-08-06T19:30:54.532717Z digest=sha256:c6ebaf40206c0dc31b602df6c0d4102706a4ec2722f0964c084a53fd85d2b9d0

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 2026-08-22T06:32:14.747728+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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:54.722508Z digest=sha256:7a073ae4506089cb0385349d63a4cbaa9c92cd6f1608d43d403e9a056cc36a94

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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local_arxiv, observed 2026-08-06T19:30:55.764300Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:54.810202Z digest=sha256:28a5dfc5c012ca07fe4bd343143096e2141316d4e651e4bfc227bcac5108f656

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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:55.069865Z digest=sha256:d89ab15b1a111d19c66eba15a1eafd319bf179a5247a2be8f46c297438c35e80

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:55.146593Z digest=sha256:d5c9a5a0589aef8247152c6dbfd176c8fa9f49202142c67f025652964f75f128

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:55.311572Z digest=sha256:fadd8ab9d088ed5b2b76dc8f51a600511f6ce9a956d4d983ea145dc4ee61a59b

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:55.386214Z digest=sha256:00ad5dfc29d5386ff84854d7d50829741b8e5d5ef639d5ec0f06fab0b134dc1c

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T19:30:55.485416Z digest=sha256:bfd3497c288486763be2f0b1b58072476b87d2a47a5184817302e3327f21df2a

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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raw_fallback, observed 2026-08-06T19:30:56.280183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

No inbound Pith citation observations are available.