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Paper Citation Record · LEDGER

U-Net in Medical Image Segmentation: A Review of Its Applications Across Modalities

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2412.02242.

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

pith.paper-citation-record.v1
2412.02242 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:08:48.984372Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:38:39.679842Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 792bf148-02a1-41ee-b6b3-0e52fb9045ce · inbound

Generative Lagrangian data assimilation for ocean dynamics under extreme sparsity cites this paper.

Generative Lagrangian data assimilation for ocean dynamics under extreme sparsity U-Net in Medical Image Segmentation: A Review of Its Applications Across Modalities

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T19:08:48.984372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:08:48.984372Z digest=sha256:5cf51fd44969607282e6d7f8db33efed016b6d6df41bd0ea7669fc7ca1fc6eba

Observation e99c6e10-e4b9-4379-b7d5-fc15207613c7 · inbound

HistoSeg++: Delving deeper with attention and multiscale feature fusion for biomarker segmentation cites this paper.

HistoSeg++: Delving deeper with attention and multiscale feature fusion for biomarker segmentation U-Net in Medical Image Segmentation: A Review of Its Applications Across Modalities

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:38:39.681230Z

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.

source=pdf_text observed=2026-07-03T16:34:39.823131Z digest=sha256:9606d0112eae5b48b676672e89f975c44992399bdb0f19d08e71fbb1cde1d1f9

Observation a93bde29-5667-4f59-a02d-a7a38031c16d · inbound

Learning-based Hierarchical Tracheal Anatomy Understanding from Sparse Surgical Demonstration Annotations for Ultrasound Robots cites this paper.

Learning-based Hierarchical Tracheal Anatomy Understanding from Sparse Surgical Demonstration Annotations for Ultrasound Robots U-Net in Medical Image Segmentation: A Review of Its Applications Across Modalities

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-01T05:19:57.191333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T05:19:57.191333Z digest=sha256:eab6e7345fa6e0eea24e634c9dcefb3c1777a547964c5df22e4a1cc69daf8f7d