DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder | Paper Citation Record

Observation 5998e5b3-1da2-44cb-a58d-c70aa69eab75 · outbound

This paper cites Liu, and Yansong Duan.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Liu, and Yansong Duan

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:05.022164Z

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Observation 1d8d816d-6652-4dda-8a19-33694608688c · outbound

This paper cites Lrfnet: A real-time medical image fusion method guided by detail information.Computers in biology and medicine, 173:108381, 2024.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Lrfnet: A real-time medical image fusion method guided by detail information.Computers in biology and medicine, 173:108381, 2024

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:05.009735Z

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Observation d51fd466-ab8e-437d-936f-1de3e7575a80 · outbound

This paper cites On the use of the sos metaheuristic algorithm in hybrid image fusion methods to achieve optimum spectral fidelity.International Journal of Remote Sensing, 41:3993 – 4021, 2020.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder On the use of the sos metaheuristic algorithm in hybrid image fusion methods to achieve optimum spectral fidelity.International Journal of Remote Sensing, 41:3993 – 4021, 2020

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.997426Z

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Observation b5367bd2-f82d-4917-a14c-cb191541c9b1 · outbound

This paper cites Joint image fusion and denoising via three-layer decomposition and sparse representation.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Joint image fusion and denoising via three-layer decomposition and sparse representation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.984539Z

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Observation 9533b3c0-21ff-4dc3-9080-708b3aadc246 · outbound

This paper cites F-darts: Foveated differentiable architecture search based multimodal medical image fusion.IEEE Transactions on Medical Imaging, 42:3348–3361, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder F-darts: Foveated differentiable architecture search based multimodal medical image fusion.IEEE Transactions on Medical Imaging, 42:3348–3361, 2023

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.972435Z

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Observation 2f6de8e1-aa3e-476b-9739-e438aee066a5 · outbound

This paper cites Ifsepr: A general framework for image fusion based on separate representation learning.IEEE Transactions on Multimedia, 25:608–623, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Ifsepr: A general framework for image fusion based on separate representation learning.IEEE Transactions on Multimedia, 25:608–623, 2023

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.960996Z

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Observation ebe3c482-bd5f-4113-81d0-4df158af8512 · outbound

This paper cites Multimodal medical image fusion based on multichannel coupled neural p systems and max-cloud models in spectral total variation domain.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Multimodal medical image fusion based on multichannel coupled neural p systems and max-cloud models in spectral total variation domain

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.949243Z

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Observation 2dee87be-ab00-4f48-9642-10849a58e62b · outbound

This paper cites an unresolved cited work.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:45:04.937971Z

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Observation 6f237cb7-f73c-48a0-99ec-0e016d85c495 · outbound

This paper cites A novel approach based on grasshopper optimization algorithm for medical image fusion.Expert Syst.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder A novel approach based on grasshopper optimization algorithm for medical image fusion.Expert Syst

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.926372Z

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Observation c7ac8cff-8603-4f22-aa40-e44c71c65b87 · outbound

This paper cites A new approach to medical image fusion based on the improved extended difference-of-gaussians combined with the coati optimization algorithm.Biomed.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder A new approach to medical image fusion based on the improved extended difference-of-gaussians combined with the coati optimization algorithm.Biomed

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.914202Z

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Observation 2e82a5c4-225a-4057-bcb8-b06a02a6c0ce · outbound

This paper cites Densefuse: A fusion approach to infrared and visible images.IEEE TIP, 28:2614–2623, 2018.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Densefuse: A fusion approach to infrared and visible images.IEEE TIP, 28:2614–2623, 2018

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.901083Z

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Observation a033f421-c88f-4a27-9bf6-fb3f315c613b · outbound

This paper cites Ifcnn: A general image fusion framework based on convolutional neural network.Inf.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Ifcnn: A general image fusion framework based on convolutional neural network.Inf

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.888357Z

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Observation 5f44af11-e2a0-4e76-9957-78236cd8ec2d · outbound

This paper cites Dfenet: A dual-branch feature enhanced network integrating transform- ers and convolutional feature learning for multimodal medical image fusion.Biomed.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Dfenet: A dual-branch feature enhanced network integrating transform- ers and convolutional feature learning for multimodal medical image fusion.Biomed

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.876457Z

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Observation 556484eb-2f7b-4185-969b-9ba2cdfc5201 · outbound

This paper cites Fu, Baiqing He, Jie Yang, Jianpeng Liu, Aijia Ouyang, and Ya Wang.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Fu, Baiqing He, Jie Yang, Jianpeng Liu, Aijia Ouyang, and Ya Wang

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.864910Z

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Observation a8399387-cc90-4dde-91be-370b01e0be71 · outbound

This paper cites Multi-level difference information replenishment for medical image fusion.Applied Intelligence, 53:4579–4591, 2022.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Multi-level difference information replenishment for medical image fusion.Applied Intelligence, 53:4579–4591, 2022

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.851620Z

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Observation 3320170c-f324-4bd1-947c-668a37566076 · outbound

This paper cites Mactfusion: Lightweight cross transformer for adaptive multimodal medical image fusion.IEEE journal of biomedical and health informatics, PP, 2024.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Mactfusion: Lightweight cross transformer for adaptive multimodal medical image fusion.IEEE journal of biomedical and health informatics, PP, 2024

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.839984Z

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Observation 4a234f3a-6c3f-4b85-8cbd-24409954c5c0 · outbound

This paper cites Liu, Yansong Duan, and Tongzhen Si.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Liu, Yansong Duan, and Tongzhen Si

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.828088Z

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Observation c4116d4a-f424-481a-a052-f4a9d383b91d · outbound

This paper cites an unresolved cited work.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:45:04.816433Z

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Observation 8559f459-a7e8-41af-aa79-edf0b0fa8da8 · outbound

This paper cites an unresolved cited work.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:45:04.804534Z

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Observation 88ec8b1a-358c-41f1-8f5a-7f9782348fba · outbound

This paper cites FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion with Mamba.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion with Mamba

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T19:45:04.002049Z

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Observation 6dfe1540-0806-41b0-91a6-fc15af826837 · outbound

This paper cites Dsagan: A generative adversarial network based on dual-stream attention mechanism for anatomical and functional image fusion.Inf.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Dsagan: A generative adversarial network based on dual-stream attention mechanism for anatomical and functional image fusion.Inf

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.792297Z

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Observation 5c0bcbd7-4612-4169-be3c-e131e7b5b293 · outbound

This paper cites Ddcgan: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion.IEEE Transactions on Image Processing, 29:4980–4995, 2020.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Ddcgan: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion.IEEE Transactions on Image Processing, 29:4980–4995, 2020

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.780246Z

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Observation 67850553-0f26-4754-b49b-5c6b248b23c3 · outbound

This paper cites Unified gradient- and intensity-discriminator generative adversarial net- work for image fusion.Inf.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unified gradient- and intensity-discriminator generative adversarial net- work for image fusion.Inf

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.767568Z

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Observation dd5571f2-135e-4263-aba0-68787964045b · outbound

This paper cites Glioma segmentation-oriented multi-modal mr image fusion with adversarial learning.IEEE CAA J.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Glioma segmentation-oriented multi-modal mr image fusion with adversarial learning.IEEE CAA J

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.755182Z

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Observation eb16c90d-2eb9-4551-a3a4-2d5807cce7d2 · outbound

This paper cites Coconet: Coupled contrastive learning network with multi-level feature ensemble for multi-modality image fusion.IJCV ., 132:1748– 1775, 2022.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Coconet: Coupled contrastive learning network with multi-level feature ensemble for multi-modality image fusion.IJCV ., 132:1748– 1775, 2022

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.743296Z

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Observation 5597c4ca-d36a-45c2-ae34-f088350c34c6 · outbound

This paper cites Self-supervised fusion for multi-modal medical images via contrastive auto-encoding and convolutional information exchange.IEEE Computational Intelligence Magazine, 18:68–80, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Self-supervised fusion for multi-modal medical images via contrastive auto-encoding and convolutional information exchange.IEEE Computational Intelligence Magazine, 18:68–80, 2023

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.730807Z

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Observation 6632b9ec-ca36-4c2d-9ee5-6094c7b60d4f · outbound

This paper cites an unresolved cited work.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:45:04.718851Z

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Observation c1b53499-a26b-4a7b-914b-b061842ef66a · outbound

This paper cites A general paradigm with detail-preserving conditional invertible network for image fusion.International Journal of Computer Vision, 132(4):1029–1054, 2024.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder A general paradigm with detail-preserving conditional invertible network for image fusion.International Journal of Computer Vision, 132(4):1029–1054, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.707476Z

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Observation ed7e8b5b-0873-46f9-a621-a66092cc225a · outbound

This paper cites Mmif-inet: Multimodal medical image fusion by invertible network.Inf.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Mmif-inet: Multimodal medical image fusion by invertible network.Inf

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.694509Z

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Observation 2079dbe1-8e42-47b6-8d50-34fa6d5ababb · outbound

This paper cites An efficient approach to medical image fusion based on optimization and transfer learning with vgg19.Biomed.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder An efficient approach to medical image fusion based on optimization and transfer learning with vgg19.Biomed

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.682089Z

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Observation 62700110-2780-4811-8e97-4db797a92643 · outbound

This paper cites Mif-btf-mrn: Medical image fusion based on the bilateral texture filter and transfer learning with the resnet-101 network.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Mif-btf-mrn: Medical image fusion based on the bilateral texture filter and transfer learning with the resnet-101 network

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.670157Z

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Observation 03bda38a-7f3f-4bf1-b40b-d7a3d99844a0 · outbound

This paper cites Task-customized mixture of adapters for general image fusion.2024 IEEE/CVF Con- ference on Computer Vision and Pattern Recognition (CVPR), pages 7099–7108, 2024.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Task-customized mixture of adapters for general image fusion.2024 IEEE/CVF Con- ference on Computer Vision and Pattern Recognition (CVPR), pages 7099–7108, 2024

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.658610Z

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Observation f0052fee-4149-4cda-988d-cbdd618ca248 · outbound

This paper cites Zhang, Ren qi Nie, Jinde Cao, Chaozhen Ma, and Chengchao Wang.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Zhang, Ren qi Nie, Jinde Cao, Chaozhen Ma, and Chengchao Wang

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.647367Z

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Observation 113ea359-c1d6-47c6-a5f8-7f433b5eb239 · outbound

This paper cites Emfusion: An unsupervised enhanced medical image fusion network.Inf.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Emfusion: An unsupervised enhanced medical image fusion network.Inf

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.636188Z

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Observation efd8ee82-dd2c-4060-8a85-3081647c3919 · outbound

This paper cites Gesenet: A general semantic-guided network with couple mask ensemble for medical image fusion.IEEE transactions on neural networks and learning systems, PP, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Gesenet: A general semantic-guided network with couple mask ensemble for medical image fusion.IEEE transactions on neural networks and learning systems, PP, 2023

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.625216Z

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Observation 418a361b-2394-4167-909a-cc6803a81c8c · outbound

This paper cites Sdnet: A versatile squeeze-and-decomposition network for real-time image fusion.International Journal of Computer Vision, 129:2761 – 2785, 2021.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Sdnet: A versatile squeeze-and-decomposition network for real-time image fusion.International Journal of Computer Vision, 129:2761 – 2785, 2021

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.614330Z

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Observation 44e8f512-b994-43ce-a378-d226465ced9f · outbound

This paper cites Zhang, Deyu Meng, Radu Timofte, and Luc Van Gool.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Zhang, Deyu Meng, Radu Timofte, and Luc Van Gool

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.603226Z

Source-reported events for the cited work

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Observation 22f1ea35-8560-4064-8fc5-6a3e794fc14c · outbound

This paper cites Fusiondiff: Multi-focus image fusion using denoising diffusion probabilistic models.Expert Syst.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Fusiondiff: Multi-focus image fusion using denoising diffusion probabilistic models.Expert Syst

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.592183Z

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Observation e0d74696-a33a-4678-8aaa-aa8602e53ae2 · outbound

This paper cites Dif-fusion: Toward high color fidelity in infrared and visible image fusion with diffusion models.IEEE Transactions on Image Processing, 32:5705– 5720, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Dif-fusion: Toward high color fidelity in infrared and visible image fusion with diffusion models.IEEE Transactions on Image Processing, 32:5705– 5720, 2023

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.580350Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0ccfe68c-5818-413d-a687-ffee88956369 · outbound

This paper cites Swinfusion: Cross-domain long-range learning for general image fusion via swin transformer.IEEE/CAA Journal of Automatica Sinica, 9:1200–1217, 2022.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Swinfusion: Cross-domain long-range learning for general image fusion via swin transformer.IEEE/CAA Journal of Automatica Sinica, 9:1200–1217, 2022

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.568232Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c3938407-c2bd-4729-8140-2d772f2d5a97 · outbound

This paper cites an unresolved cited work.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:45:04.557179Z

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Observation 29bf0629-6fdb-45fa-ab15-602891daa59c · outbound

This paper cites Ct and mri medical image fusion using noise-removal and contrast enhancement scheme with convolutional neural network.Entropy, 24, 2022.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Ct and mri medical image fusion using noise-removal and contrast enhancement scheme with convolutional neural network.Entropy, 24, 2022

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.545815Z

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Observation 6efe191c-a332-4265-bab0-fb67db90087f · outbound

This paper cites Fatfusion: A functional–anatomical transformer for medical image fusion.Information Processing & Management, 61(4):103687, 2024.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Fatfusion: A functional–anatomical transformer for medical image fusion.Information Processing & Management, 61(4):103687, 2024

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.533688Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5b1dd1c2-85a3-4892-af67-934fe01d4f8d · outbound

This paper cites Jane Wang, and Xun Chen.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Jane Wang, and Xun Chen

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.522028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6be84e54-2272-4c85-9fbd-2df3ba49abfa · outbound

This paper cites An improved hybrid JOURNAL OF LATEX CLASS FILES, VOL.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder An improved hybrid JOURNAL OF LATEX CLASS FILES, VOL

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.510481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 725027e3-d914-4e5d-9379-6493927f239d · outbound

This paper cites Denoising Diffusion Probabilistic Models.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Denoising Diffusion Probabilistic Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T19:45:04.099642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 719616d6-815d-432a-9bba-2a7e8c705d6f · outbound

This paper cites Diffusion- based network for unsupervised landmark detection.Knowl.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Diffusion- based network for unsupervised landmark detection.Knowl

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.499604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a2544feb-d11c-46e4-b9fc-76cf813f1349 · outbound

This paper cites Corrdiff: Corrective diffusion model for accurate mri brain tumor segmentation.IEEE Journal of Biomedical and Health Informatics, 28:1587–1598, 2024.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Corrdiff: Corrective diffusion model for accurate mri brain tumor segmentation.IEEE Journal of Biomedical and Health Informatics, 28:1587–1598, 2024

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.488143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 32fd402d-9fb4-405f-a31e-e3cfa69d0fb3 · outbound

This paper cites an unresolved cited work.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:45:04.475687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ba6a57f4-c2fb-43fd-860a-d4114f4186b0 · outbound

This paper cites Yang, and Chaoyue Wang.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Yang, and Chaoyue Wang

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.465039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b7c4d241-3d98-47f1-9843-a2bd562f5892 · outbound

This paper cites Acdmsr: Accelerated conditional diffusion models for single image super-resolution.IEEE Transactions on Broadcasting, 70:492–504, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Acdmsr: Accelerated conditional diffusion models for single image super-resolution.IEEE Transactions on Broadcasting, 70:492–504, 2023

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.454219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bb5af54c-ac49-4c9e-81bb-603033e386de · outbound

This paper cites an unresolved cited work.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:45:04.443828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9036d78b-8357-4073-8858-fd1f82c2f91c · outbound

This paper cites Fleet, and Mohammad Norouzi.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Fleet, and Mohammad Norouzi

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.433912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 79ae56e6-0b5a-4872-9af7-70b33dfcf729 · outbound

This paper cites Dea-net: Single image dehazing based on detail-enhanced convolution and content-guided attention.IEEE Transactions on Image Processing, 33:1002–1015, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Dea-net: Single image dehazing based on detail-enhanced convolution and content-guided attention.IEEE Transactions on Image Processing, 33:1002–1015, 2023

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.423531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cc1143ae-bc9b-4cc7-8ab8-8f1f63c426d6 · outbound

This paper cites M4fnet: Multimodal medical image fusion network via multi-receptive-field and multi-scale feature integration.Computers in biology and medicine, 159:106923, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder M4fnet: Multimodal medical image fusion network via multi-receptive-field and multi-scale feature integration.Computers in biology and medicine, 159:106923, 2023

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.412404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5dc1caba-4299-4413-85ba-713f0dea683e · outbound

This paper cites Eskicioglu and Paul S.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Eskicioglu and Paul S

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.400976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4b865367-a138-457b-8a34-a5bddf16796c · outbound

This paper cites In-fibre bragg grating sensors.Measurement Science and Technology, 8:355 – 375, 1997.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder In-fibre bragg grating sensors.Measurement Science and Technology, 8:355 – 375, 1997

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.389458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 926d7155-4998-49cd-9c79-1a070ebffa58 · outbound

This paper cites Detail preserved fusion of visible and infrared images using regional saliency extraction and multi-scale image decomposition.Optics Com- munications, 341:199–209, 2015.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Detail preserved fusion of visible and infrared images using regional saliency extraction and multi-scale image decomposition.Optics Com- munications, 341:199–209, 2015

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.377130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 67ee1680-e99d-4cc0-b805-cdb8019aa995 · outbound

This paper cites an unresolved cited work.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:45:04.365375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f8d4e630-8367-4303-8865-4ae8e373326f · outbound

This paper cites A new image quality metric for image fusion: The sum of the correlations of differences.Aeu- international Journal of Electronics and Communications, 69:1890– 1896, 2015.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder A new image quality metric for image fusion: The sum of the correlations of differences.Aeu- international Journal of Electronics and Communications, 69:1890– 1896, 2015

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.353293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2daed43e-0376-4261-ac6e-dac6f60d1d2f · outbound

This paper cites A new image fusion performance metric based on visual information fidelity.Inf.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder A new image fusion performance metric based on visual information fidelity.Inf

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.340835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6089cf93-8c64-472e-9bdc-ad1946e5657d · outbound

This paper cites Xydeas and Vladimir S.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Xydeas and Vladimir S

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.329143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ba8b1248-b751-4a0b-a3ab-7bf8fb3a370b · outbound

This paper cites Simoncelli, and Alan Conrad Bovik.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Simoncelli, and Alan Conrad Bovik

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.316627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 270b9001-cf9e-4739-9724-b6af0fe51d85 · outbound

This paper cites A non- reference image fusion metric based on mutual information of image features.Comput.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder A non- reference image fusion metric based on mutual information of image features.Comput

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.303890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 733a2495-cff6-4825-b956-f99fc8ba7d7b · outbound

This paper cites Lrrnet: A novel representation learning guided fusion network for infrared and visible images.IEEE Trans.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Lrrnet: A novel representation learning guided fusion network for infrared and visible images.IEEE Trans

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.289525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c411273b-accc-41e2-bfa1-367e76aba7dc · outbound

This paper cites Multi-interactive feature learning and a full-time multi-modality benchmark for image fusion and segmentation.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Multi-interactive feature learning and a full-time multi-modality benchmark for image fusion and segmentation

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.276753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 25f8cbbb-bdb6-49f2-925d-280813535b15 · outbound

This paper cites Correlation-guided discriminative cross-modality features network for infrared and visible image fusion.IEEE Transactions on Instrumentation and Measurement, 2023.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Correlation-guided discriminative cross-modality features network for infrared and visible image fusion.IEEE Transactions on Instrumentation and Measurement, 2023

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.263890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d5ca9bb9-82ce-49d4-98f7-9388e1e10c24 · outbound

This paper cites Probing synergistic high-order interaction in infrared and visible image fusion.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Probing synergistic high-order interaction in infrared and visible image fusion

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.252115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1b5cbf0d-4ca3-4ff4-9417-86de63c851fe · outbound

This paper cites Mmdrfuse: Distilled mini-model with dynamic refresh for multi- modality image fusion.

DM-FNet: Unified multimodal medical image fusion via diffusion process-trained encoder-decoder Mmdrfuse: Distilled mini-model with dynamic refresh for multi- modality image fusion

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:45:04.239874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Reference resolution

Outbound references

Pith citing papers