mlsanityData to 7 Oct 2026

Medical Image Fusion: A survey of the state of the art

arXiv 1401.0166 ↗First posted 31 Dec 2013cs.CV cs.AI physics.med-phcited by 39

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Abstract (arXiv)

Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multi-modal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. This review article provides a factual listing of methods and summarizes the broad scientific challenges faced in the field of medical image fusion. We characterize the medical image fusion research based on (1) the widely used image fusion methods, (2) imaging modalities, and (3) imaging of organs that are under study. This review concludes that even though there exists several open ended technological and scientific challenges, the fusion of medical images has proved to be useful for advancing the clinical reliability of using medical imaging for medical diagnostics and analysis, and is a scientific discipline that has the potential to significantly grow in the coming years.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Dec 2013.

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Citing papers per year: 2021: 9; 2022: 4; 2023: 6; 2024: 7; 2025: 9; 2026: 4.

39 papers.

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  1. 2022CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusioncited by 222
  2. 2023DDFM: Denoising Diffusion Model for Multi-Modality Image Fusioncited by 153
  3. 2023Equivariant Multi-Modality Image Fusioncited by 98
  4. 2022MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray imagescited by 53
  5. 2024Image Fusion via Vision-Language Modelcited by 40
  6. 2024MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image Fusioncited by 35
  7. 2021Modality specific U-Net variants for biomedical image segmentation: A surveycited by 20
  8. 2022Multi-Modality Cardiac Image Computing: A Surveycited by 19
  9. 2023ReFusion: Learning Image Fusion from Reconstruction with Learnable Loss via Meta-Learningcited by 15
  10. 2023Dynamic Enhancement Network for Partial Multi-modality Person Re-identificationcited by 9
  11. 2021UncertaintyFuseNet: Robust Uncertainty-aware Hierarchical Feature Fusion Model with Ensemble Monte Carlo Dropout for COVID-19 Detectioncited by 8
  12. 2025A Unified Solution to Video Fusion: From Multi-Frame Learning to Benchmarkingcited by 8
27 more
  1. 2024Test-Time Dynamic Image Fusioncited by 6
  2. 2025Spatial-Frequency Enhanced Mamba for Multi-Modal Image Fusioncited by 5
  3. 2021Coupled Feature Learning for Multimodal Medical Image Fusioncited by 4
  4. 2024DAE-Fuse: An Adaptive Discriminative Autoencoder for Multi-Modality Image Fusioncited by 4
  5. 2021Unsupervised Image Fusion Using Deep Image Priorscited by 2
  6. 2025A Comprehensive Review of Techniques, Algorithms, Advancements, Challenges, and Clinical Applications of Multi-modal Medical Image Fusion for Improved Diagnosiscited by 2
  7. 2021Feature Fusion of Raman Chemical Imaging and Digital Histopathology using Machine Learning for Prostate Cancer Detectioncited by 1
  8. 2021Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusionscited by 1
  9. 2021Variable Augmented Network for Invertible Modality Synthesis-Fusioncited by 1
  10. 2021Multispectral image fusion based on super pixel segmentationcited by 1
  11. 2025SMFusion: Semantic-Preserving Fusion of Multimodal Medical Images for Enhanced Clinical Diagnosiscited by 1
  12. 2025Single Domain Generalization for Alzheimer's Detection from 3D MRIs with Pseudo-Morphological Augmentations and Contrastive Learningcited by 1
  13. 2025Text-Guided Channel Perturbation and Pretrained Knowledge Integration for Unified Multi-Modality Image Fusioncited by 1
  14. 2021Semantic Image Fusioncited by 0
  15. 2022Multimodal Query-guided Object Localizationcited by 0
  16. 2023Decomposing and Coupling Saliency Map for Lesion Segmentation in Ultrasound Imagescited by 0
  17. 2023Three-Dimensional Medical Image Fusion with Deformable Cross-Attentioncited by 0
  18. 2024GAN-HA: A generative adversarial network with a novel heterogeneous dual-discriminator network and a new attention-based fusion strategy for infrared and visible image fusioncited by 0
  19. 2024SimpleFusion: A Simple Fusion Framework for Infrared and Visible Imagescited by 0
  20. 2024Fuse4Seg: Image Fusion for Multi-Modal Medical Segmentation via Bi-level Optimizationcited by 0
  21. 2025COph100: A comprehensive fundus image registration dataset from infants constituting the "RIDIRP" databasecited by 0
  22. 2025Rethinking Few-Shot Image Fusion: Granular Ball Priors Enable General-Purpose Deep Fusioncited by 0
  23. 2025MMIF-AMIN: Adaptive Loss-Driven Multi-Scale Invertible Dense Network for Multimodal Medical Image Fusioncited by 0
  24. 2026AMIF: Authorizable Medical Image Fusion Model with Built-in Authenticationcited by 0
  25. 2026MedXplore: Towards Reliable and Unbiased Generalized Category Discovery in Medical Imagingcited by 0
  26. 2026MIND: Multimodal Intent-Driven Network via Diffusion Transformers for Medical Image Fusioncited by 0
  27. 2026UniDiffFusion: A Unified Diffusion Framework for Multi-Task and Degradation-Robust Image Fusioncited by 0