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September 19, 2025IEEE Journal of Biomedical and Health Informatics

Mamba-Enhanced Diffusion Model for Perception-Aware Blind Super-Resolution of Magnetic Resonance Imaging

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Authors

XZXiaoqiang ZhaoXYXiaodong YangZSZhaoyang Song

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Overview

This approach improves super-resolution outcomes in MRI by leveraging a diffusion model and semantic fusion techniques.

Key Points

  • The Mamba-enhanced Diffusion Model achieves superior super-resolution in MRI, enhancing image clarity for better diagnosis.
  • Extensive experiments confirmed that the proposed method outperforms existing techniques in reconstructing high-resolution images.
  • The method integrates a Perception-aware Blur Kernel Noise estimator, which effectively estimates blur from low-resolution inputs.
  • A novel SIF-Mamba module enhances feature reconstruction by capturing the global context within MRI images.

Cite This Study

Zhao et al. (2025) studied this question.

synapsesocial.com/papers/68d464ea31b076d99fa64195https://doi.org/10.1109/jbhi.2025.3611232
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Also Consider

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

  1. 1Efficient vision mamba for MRI super‐resolution via hybrid selective scanning2026
  2. 2Kernel-Aware Network with Dual Diffusion Model for MRI Blind Super Resolution2025
  3. 3MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting2025
  4. 4Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution2024
  5. 5Dual-Domain Multipath Self-Supervised Diffusion Model for Accelerated MRI Reconstruction2026