UniFuse: A Unified All-in-One Framework for Multi-Modal Medical Image Fusion Under Diverse Degradations and Misalignments | Paper Citation Record

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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 2026-08-19T06:32:44.657259+00:00.

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