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May 6, 2026Applied SciencesOpen Access

Accelerated Edge-Aware Diffusion Model with Spatial Refinement for Clinical Medical Image Fusion

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Authors

WQWeiyan QuanJLJingjing Liu

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Overview

The proposed model improves image fusion quality in clinical settings, suggesting enhanced processing capabilities.

Key Points

  • To improve the speed and quality of clinical medical image fusion using an edge-aware diffusion model.
  • Developed an accelerated edge-aware diffusion model with spatial refinement.
  • Utilized edge-enhanced data blocks and non-uniform time-step sampling.
  • Implemented a Nesterov accelerated alternating direction method for pixel-level corrections.
  • Achieved approximately 42% faster inference time compared to the baseline.
  • Demonstrated superior performance in image fidelity and structural preservation.
  • Effectively merged soft tissue textures and skeletal contours in medical images.

Cite This Study

Quan et al. (2026) studied this question.

synapsesocial.com/papers/69faa28f04f884e66b533350https://doi.org/10.3390/app16094397
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1DF-DiffVSR: Deformable Field-Driven Diffusion Model for Inter-Slice Continuity Enhancement in Medical Volume Super-Resolution2026
  2. 2Advancing multimodal medical image fusion: an adaptive image decomposition approach based on multilevel Guided filtering2024 · 11 citations
  3. 3Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using Conditional Diffusion Model2024
  4. 4Clinically Feasible Diffusion Reconstruction for Highly-Accelerated Cardiac Cine MRI2024
  5. 5Structure-aware medical image fusion via mean curvature enhancement in the contourlet domain2025 · 1 citations