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Paper Citation Record · LEDGER

GANs for Medical Image Synthesis: An Empirical Study

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2105.05318.

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

pith.paper-citation-record.v1
2105.05318 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:54:10.816048Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:24:56.137685Z

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 fecc8fe2-29ab-4cda-abe7-c876ef31c565 · inbound

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation cites this paper.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation GANs for Medical Image Synthesis: An Empirical Study

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-15T22:54:10.816048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:54:10.816048Z digest=sha256:56ff3459ab8b69c5e1081c94d7bda929d737400adb68d8df663b1931e7ade524

Observation d86b01d1-130e-41bd-a1ec-c1846e2f23af · inbound

F3-Net: Foundation Model for Full Abnormality Segmentation of Medical Images with Flexible Input Modality Requirement cites this paper.

F3-Net: Foundation Model for Full Abnormality Segmentation of Medical Images with Flexible Input Modality Requirement GANs for Medical Image Synthesis: An Empirical Study

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:24:56.181848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T18:24:51.847791Z digest=sha256:bac3074a5be5f91604cc547079525632656504002474858e6b9e72d22e94b8cc