Paper Citation Record · LEDGER

Brain Imaging Generation with Latent Diffusion Models

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2209.07162.

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

pith.paper-citation-record.v1
2209.07162 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:42:31.491670Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T10:27:02.506289Z

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 6879a460-6cf6-49c6-96f9-5b81c57bf6f0 · inbound

Standardisation of Convex Ultrasound Data Through Geometric Analysis and Augmentation cites this paper.

Standardisation of Convex Ultrasound Data Through Geometric Analysis and Augmentation Brain Imaging Generation with Latent Diffusion Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T21:23:20.435023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37b7fb50-0ffc-4713-8420-5a1b2a9197f6 · inbound

DustNET: enabling machine learning and AI models of dusty plasmas cites this paper.

DustNET: enabling machine learning and AI models of dusty plasmas Brain Imaging Generation with Latent Diffusion Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:59:52.886819Z

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.

Observation 88068724-5760-466e-802e-02441b1932e5 · inbound

Triple-Phase Sequential Fusion Network for Hepatobiliary Phase Liver MRI Synthesis cites this paper.

Triple-Phase Sequential Fusion Network for Hepatobiliary Phase Liver MRI Synthesis Brain Imaging Generation with Latent Diffusion Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:26:11.541880Z

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.

Observation f8483c8e-06f8-49b4-996f-19f40c403174 · inbound

Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025 cites this paper.

Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025 Brain Imaging Generation with Latent Diffusion Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:55:23.526123Z

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.

Observation b51b727c-541f-4b3f-9f94-3fa3a4140394 · inbound

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation cites this paper.

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation Brain Imaging Generation with Latent Diffusion Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-04T01:19:21.152156Z

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.

Observation 958a9152-43f5-4b7a-a8f0-1458f6b36c0e · inbound

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation cites this paper.

BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation Brain Imaging Generation with Latent Diffusion Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T10:53:56.921692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a09ee8d7-9b98-4186-a10a-b7c75be335f2 · inbound

Progression as Latent Drift: Generative Forecasting of Slow-Evolving Pathologies cites this paper.

Progression as Latent Drift: Generative Forecasting of Slow-Evolving Pathologies Brain Imaging Generation with Latent Diffusion Models

Reference 41

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T10:27:02.507528Z

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.

Observation a9c85505-ce25-4170-b7b1-80a040b53a69 · inbound

Anatomically Consistent Cross-Contrast Super-Resolution of Anisotropic Brain T2w MRI cites this paper.

Anatomically Consistent Cross-Contrast Super-Resolution of Anisotropic Brain T2w MRI Brain Imaging Generation with Latent Diffusion Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T04:42:31.491670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.