Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2209.12104.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:56:46.889987Z
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 14030778-03e2-4a3c-b66d-28405a3d80f3 · inbound
Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review cites this paper.
Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models
Reference 145
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:56:46.889987Z
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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+00:00.