Paper Citation Record · LEDGER

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning

As of 6 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2509.10784.

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

pith.paper-citation-record.v1
2509.10784 v3

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T17:26:20.808210Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T17:52:58.049670Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-02T23:47:27.968848Z

Reference resolution

12 of 12 outbound references displayed

verified exact1
verified fuzzy5
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 081e7918-f739-46f2-88ef-c1eb04151d35 · outbound

This paper cites Du,Z.,Li,J.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning Du,Z.,Li,J

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T17:26:40.714937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fe7397bb-643f-4016-89e6-98949d5897c3 · outbound

This paper cites How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T17:26:40.306783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 76f8d405-a707-4d3f-9910-e950bd711040 · outbound

This paper cites Medical Image Analysis 82, 102616.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning Medical Image Analysis 82, 102616

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T17:26:40.705516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ac76cd93-8e23-415b-b787-db1552c8b1f2 · outbound

This paper cites Nature 616, 259–265.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning Nature 616, 259–265

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T17:26:40.708774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 40c24125-5493-4bc0-95ce-4472efccf63f · outbound

This paper cites Vision Foundation Models for Computed Tomography.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning Vision Foundation Models for Computed Tomography

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T17:26:40.311098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation de4352ae-c7cb-4e18-bb0a-f0337cb03997 · outbound

This paper cites an unresolved cited work.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-05-18T17:26:40.711768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1c2433b3-0cc1-433a-952a-25fe4e050ba2 · outbound

This paper cites 9433–9443.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning 9433–9443

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T17:26:40.693029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 20ad94cb-fcef-4167-b3bd-18cc59dbfeb8 · outbound

This paper cites Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T17:26:40.315462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5c2c7a02-8eae-42b4-b43a-fc407a7fdfd4 · outbound

This paper cites an unresolved cited work.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-05-18T17:26:40.702249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4922cbfd-a876-4f9c-8d59-d36cf88f6109 · outbound

This paper cites an unresolved cited work.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-05-18T17:26:40.696088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation df56498b-c92d-4a28-8168-2e0a03f18105 · outbound

This paper cites RadiologyAdvances 2, umae035.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning RadiologyAdvances 2, umae035

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T17:26:40.699276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6d98116f-ff99-4ced-a320-4bc348a47b35 · outbound

This paper cites 3D Foundation Model for Generalizable Disease Detection in Head Computed Tomography.

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning 3D Foundation Model for Generalizable Disease Detection in Head Computed Tomography

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T17:26:40.319150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation b24db503-c485-4a53-9228-4050cf11fcdf · inbound

Active Source-free Domain Adaptation in Open-set Medical Image Segmentation via Decomposed Uncertainty and Prototype Discrepancy cites this paper.

Active Source-free Domain Adaptation in Open-set Medical Image Segmentation via Decomposed Uncertainty and Prototype Discrepancy Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T23:47:27.970146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.