Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:05:00.064020Z
Paper Citation Record · LEDGER
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments
As of 9 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.22736.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
44 of 44 outbound references displayed
- verified exact0
- verified fuzzy41
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 9ddd0fc3-e6a5-439b-8586-ad596a7fdc12 · outbound
This paper cites A new image quality met- ric for image fusion: The sum of the correlations of differ- ences.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments A new image quality met- ric for image fusion: The sum of the correlations of differ- ences
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:08.209208Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 3bb48bda-8240-4d11-9d1d-4d6759b05026 · outbound
This paper cites V oxelmorph: a learning framework for deformable medical image registration.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments V oxelmorph: a learning framework for deformable medical image registration
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:08.051722Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 59b2da77-0886-4d42-8213-afff22ec71f0 · outbound
This paper cites Transmorph: Transformer for unsuper- vised medical image registration.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Transmorph: Transformer for unsuper- vised medical image registration
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:07.898638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f4e41761-bc83-434a-a748-4d55fcbefd5c · outbound
This paper cites Ammnet: A multimodal medical image fusion method based on an attention mechanism and mobilenetv3.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Ammnet: A multimodal medical image fusion method based on an attention mechanism and mobilenetv3
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:07.742114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 04d5a79a-f35e-4da0-b273-ac692863684d · outbound
This paper cites Learning federated visual prompt in null space for mri reconstruction.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Learning federated visual prompt in null space for mri reconstruction
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:07.653558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation fc811732-c6b4-4c33-8c74-8822301ca032 · outbound
This paper cites A whole-body fdg-pet/ct dataset with manu- ally annotated tumor lesions.Scientific Data, 9(1):601, 2022.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments A whole-body fdg-pet/ct dataset with manu- ally annotated tumor lesions.Scientific Data, 9(1):601, 2022
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:07.480120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 086ff80f-4cc3-4104-bf81-68f80589e34e · outbound
This paper cites Adaptive spatial and frequency experts fusion network for medical image fusion.Biomedical Signal Processing and Control, 96:106478, 2024.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Adaptive spatial and frequency experts fusion network for medical image fusion.Biomedical Signal Processing and Control, 96:106478, 2024
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:07.286606Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 1b242904-2a2b-4d1e-8158-5ad3729196b6 · outbound
This paper cites Adaptive diffusion priors for accelerated mri reconstruction.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Adaptive diffusion priors for accelerated mri reconstruction
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:07.112274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 0766ffcc-a441-4f0d-97ff-4c98f610052e · outbound
This paper cites A new im- age fusion performance metric based on visual information fidelity.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments A new im- age fusion performance metric based on visual information fidelity
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:06.915629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation db8f2218-397a-48f6-80d7-495524f6736b · outbound
This paper cites Contrastive diffusion model with auxiliary guidance for coarse-to-fine pet reconstruction.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Contrastive diffusion model with auxiliary guidance for coarse-to-fine pet reconstruction
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:06.743651Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b2171c49-5403-4f69-860b-c86c0416f6ba · outbound
This paper cites Reconet: Recurrent correction network for fast and efficient multi-modality image fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Reconet: Recurrent correction network for fast and efficient multi-modality image fusion
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:06.549692Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6e40c233-171e-4d0f-aabd-2bf0bb4f8556 · outbound
This paper cites Peak signal-to-noise ratio revisited: Is simple beautiful? In 2012 Fourth international workshop on quality of multimedia experience, pages 37–38.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Peak signal-to-noise ratio revisited: Is simple beautiful? In 2012 Fourth international workshop on quality of multimedia experience, pages 37–38
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:06.409428Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a2c96e3b-c58d-45c9-8b5a-79219e5b5341 · outbound
This paper cites Deep unfolding convolutional dictionary model for multi- contrast mri super-resolution and reconstruction.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Deep unfolding convolutional dictionary model for multi- contrast mri super-resolution and reconstruction
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:06.249588Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8c90ea21-74c6-4319-81ca-df9313f80816 · outbound
This paper cites Feature dynamic alignment and refinement for infrared–visible image fusion: Translation robust fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Feature dynamic alignment and refinement for infrared–visible image fusion: Translation robust fusion
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:06.090407Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 37f2eed2-361e-43f8-9255-036ecb3b94ba · outbound
This paper cites A deep learning framework for infrared and visible image fusion without strict registration.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments A deep learning framework for infrared and visible image fusion without strict registration
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:05.963489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 0af954cc-7a45-46f9-b803-49260436a2bb · outbound
This paper cites Bsafu- sion: A bidirectional stepwise feature alignment network for unaligned medical image fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Bsafu- sion: A bidirectional stepwise feature alignment network for unaligned medical image fusion
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:05.844343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 3c6986dc-2ea4-4e6a-a17a-e10db4a27ece · outbound
This paper cites Mulfs-cap: Multimodal fusion- supervised cross-modality alignment perception for unreg- istered infrared-visible image fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Mulfs-cap: Multimodal fusion- supervised cross-modality alignment perception for unreg- istered infrared-visible image fusion
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:05.696441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 20f634d8-5e0c-4995-8292-5081f6cf9817 · outbound
This paper cites Dfenet: A dual-branch feature enhanced network integrating transformers and convolutional feature learning for multimodal medical image fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Dfenet: A dual-branch feature enhanced network integrating transformers and convolutional feature learning for multimodal medical image fusion
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:05.510200Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ef1e220e-4259-42dc-a9e3-54701f1fe544 · outbound
This paper cites Quad-net: Quad-domain network for ct metal artifact reduction.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Quad-net: Quad-domain network for ct metal artifact reduction
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:05.367799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c4f50164-e928-44ef-83e1-8b1bb4a4a0da · outbound
This paper cites Swinir: Image restoration us- ing swin transformer.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Swinir: Image restoration us- ing swin transformer
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:04:58.809583Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9927181-b400-4d12-93a0-b12a34f96188 · outbound
This paper cites Correlation-aware coarse-to-fine mlps for deformable med- ical image registration.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Correlation-aware coarse-to-fine mlps for deformable med- ical image registration
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:05.219218Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 27f69407-a380-4cb7-a7fc-4f7adc1e4cc9 · outbound
This paper cites Correlation-aware coarse-to-fine mlps for deformable medi- cal image registration.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Correlation-aware coarse-to-fine mlps for deformable medi- cal image registration
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:05.053992Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 4591d374-4bb8-46ad-a528-9b18bd0ad3a6 · outbound
This paper cites Comparing correlated correlation coefficients.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Comparing correlated correlation coefficients
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:04.899528Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation de9491b7-07f3-496f-99f2-8dce6c5d9d6a · outbound
This paper cites The multimodal brain tumor image segmentation benchmark (brats).
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments The multimodal brain tumor image segmentation benchmark (brats)
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:04.751399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 98b88974-fa86-4cb0-b148-e75d11d8ec66 · outbound
This paper cites Learning to search a lightweight general- ized network for medical image fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Learning to search a lightweight general- ized network for medical image fusion
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:04.603946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation aafd53df-5e2a-4845-b524-f6a2052f0cd2 · outbound
This paper cites A k-space model of movement artefacts: application to segmentation augmen- tation and artefact removal.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments A k-space model of movement artefacts: application to segmentation augmen- tation and artefact removal
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:04.424335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 184a65e2-d7cc-43ff-9b69-b6b74dea3dd4 · outbound
This paper cites Destrans: A medical image fusion method based on trans- former and improved densenet.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Destrans: A medical image fusion method based on trans- former and improved densenet
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:04.138644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c610d12f-16a1-41d2-a5ee-d2d432f56f1c · outbound
This paper cites Matr: Mul- timodal medical image fusion via multiscale adaptive trans- former.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Matr: Mul- timodal medical image fusion via multiscale adaptive trans- former
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:03.928184Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 55ac3ed3-3958-4055-8e8b-e27e9c697f01 · outbound
This paper cites Syn- thrad2023 grand challenge dataset: Generating synthetic ct for radiotherapy.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Syn- thrad2023 grand challenge dataset: Generating synthetic ct for radiotherapy
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:03.702069Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 73213045-a59b-4fa3-a274-b04d9a690ff7 · outbound
This paper cites Oscnet: Orientation-shared convolu- tional network for ct metal artifact learning.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Oscnet: Orientation-shared convolu- tional network for ct metal artifact learning
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:03.359719Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a348bdc8-fad9-45e2-83d8-bd373db2e3cc · outbound
This paper cites Image quality assessment: from error visibility to structural similarity.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Image quality assessment: from error visibility to structural similarity
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:04:59.398297Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d986e551-2b3c-41a6-9229-d27642a58278 · outbound
This paper cites Pnd-net: Physics-inspired non-local dual- domain network for metal artifact reduction.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Pnd-net: Physics-inspired non-local dual- domain network for metal artifact reduction
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:03.003165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7ceaf128-5d3f-42ee-b12b-e164a3517609 · outbound
This paper cites Fusionmamba: Dynamic feature enhancement for mul- timodal image fusion with mamba.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Fusionmamba: Dynamic feature enhancement for mul- timodal image fusion with mamba
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:02.471187Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation af753883-72c3-457a-828d-8072ab92e80b · outbound
This paper cites Murf: Mutually re- inforcing multi-modal image registration and fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Murf: Mutually re- inforcing multi-modal image registration and fusion
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:02.192090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ab74ef3d-3092-4970-b324-59bc9054e0c4 · outbound
This paper cites All- in-one medical image restoration via task-adaptive routing.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments All- in-one medical image restoration via task-adaptive routing
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:01.957905Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 0967dfcf-cb54-4a47-9fd2-5b699a651ac0 · outbound
This paper cites Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKV.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKV
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:04:59.668815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4a82827e-3d6f-4b8f-99cf-482f5a5f49a7 · outbound
This paper cites F-darts: Foveated differentiable architecture search based multimodal medical image fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments F-darts: Foveated differentiable architecture search based multimodal medical image fusion
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:01.676735Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 09ee5406-a078-45cd-8a8d-7305c81e0f91 · outbound
This paper cites A robust mutual-reinforcing framework for 3d multi- modal medical image fusion based on visual-semantic con- sistency.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments A robust mutual-reinforcing framework for 3d multi- modal medical image fusion based on visual-semantic con- sistency
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:01.433112Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 08e796f3-f6c1-4947-ab19-759c2044957d · outbound
This paper cites Adaptive and itera- tive learning with multi-perspective regularizations for metal artifact reduction.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Adaptive and itera- tive learning with multi-perspective regularizations for metal artifact reduction
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:01.228541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8333cf1e-d33f-461e-8a16-aac8879de0ae · outbound
This paper cites Self-supervised deep learning for joint 3d low-dose pet/ct image denoising.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Self-supervised deep learning for joint 3d low-dose pet/ct image denoising
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:01.063935Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation cdbfc91b-cb72-4b03-abf0-07381c0a0d74 · outbound
This paper cites Equivariant multi-modality image fusion.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Equivariant multi-modality image fusion
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:00.900377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f6fd6902-e682-4509-b78e-b424d518c0c7 · outbound
This paper cites Unsupervised fusion of misaligned pat and mri images via mutually reinforcing cross-modality image generation and registration.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Unsupervised fusion of misaligned pat and mri images via mutually reinforcing cross-modality image generation and registration
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:00.735115Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 89a01ee5-2ab1-4a6d-806b-5d23aeaca486 · outbound
This paper cites Dudoufnet: dual-domain under-to-fully-complete progressive restoration network for simultaneous metal artifact reduction and low-dose ct recon- struction.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Dudoufnet: dual-domain under-to-fully-complete progressive restoration network for simultaneous metal artifact reduction and low-dose ct recon- struction
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:00.520907Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 48f8b5a5-15af-4d5d-9687-07a2e993910f · outbound
This paper cites Federated transfer learning for low-dose pet denoising: a pilot study with sim- ulated heterogeneous data.
UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments Federated transfer learning for low-dose pet denoising: a pilot study with sim- ulated heterogeneous data
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:05:00.234162Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.