Paper Citation Record · LEDGER

Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2209.12104.

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

pith.paper-citation-record.v1
2209.12104 v2

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 2026-08-13T06:32:02.005865+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:54:32.650612Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

53
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 72d127d6-3c6c-4d66-9fed-fb72bb64e8a0 · inbound

DeepSPV: A Deep Learning Pipeline for 3D Spleen Volume Estimation from 2D Ultrasound Images cites this paper.

DeepSPV: A Deep Learning Pipeline for 3D Spleen Volume Estimation from 2D Ultrasound Images Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-12T18:54:32.650612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af2bbf72-e9d1-469d-88d8-05f5eb60fad2 · inbound

From Diffusion to Resolution: Leveraging 2D Diffusion Models for 3D Super-Resolution Task cites this paper.

From Diffusion to Resolution: Leveraging 2D Diffusion Models for 3D Super-Resolution Task Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T13:34:23.525659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5c9d1d2-f563-4717-bc3a-57260ba64804 · inbound

FgC2F-UDiff: Frequency-guided and Coarse-to-fine Unified Diffusion Model for Multi-modality Missing MRI Synthesis cites this paper.

FgC2F-UDiff: Frequency-guided and Coarse-to-fine Unified Diffusion Model for Multi-modality Missing MRI Synthesis Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T21:59:52.174981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9998b510-4c6a-4d62-98e8-67b4bff8916d · inbound

Score-based Generative Diffusion Models to Synthesize Full-dose FDG Brain PET from MRI in Epilepsy Patients cites this paper.

Score-based Generative Diffusion Models to Synthesize Full-dose FDG Brain PET from MRI in Epilepsy Patients Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T04:16:40.760132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6e2bcb4-28f1-4a83-9197-e49feb1c0176 · inbound

MRI-to-CT synthesis using drifting models cites this paper.

MRI-to-CT synthesis using drifting models Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-14T01:33:35.072617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5e4b1de4-0925-4c59-ad20-42ce953a08cb · inbound

Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data cites this paper.

Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:21:09.713606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1e2ed848-51e0-4373-9ff3-5b6dcbc47cdb · inbound

Do We Really Need Diffusion? A Fast U-Net for Paired Medical Image Translation cites this paper.

Do We Really Need Diffusion? A Fast U-Net for Paired Medical Image Translation Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T01:50:21.305091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a85a4a29-4dd4-4fee-85e6-0a745f93f1b6 · inbound

Unpaired Deep Learning Synthesis of Photon-Counting CT Material Basis Maps from Non-contrast Energy-Integrating Abdominal CT Images cites this paper.

Unpaired Deep Learning Synthesis of Photon-Counting CT Material Basis Maps from Non-contrast Energy-Integrating Abdominal CT Images Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-04T19:10:05.200190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.