自适应扩散桥实现盲反问题高效重建，5-10步完成MRI高质量恢复。
ADOBI: Adaptive Diffusion Bridge For Blind Inverse Problems with Application to MRI Reconstruction
- 通过自适应校准未知正向模型，全程保持测量一致性。
- 仅需5-10步即可实现高质量并行MRI重建，性能达当前最优。
- 适合需要快速、高保真图像重建的医学成像场景。
扩散桥（DB）作为成像反问题的一种新方法，通过直接连接低质量与高质量图像分布实现快速采样。尽管引入测量一致性可提升性能，但现有方法在正向模型未知的盲反问题中无法维持该一致性。为此，我们提出ADOBI（自适应扩散桥），通过自适应校准未知正向模型，在整个采样过程中强制满足测量一致性。该方法仅需5-10步即可实现高质量并行磁共振成像（PMRI）重建。数值结果表明，ADOBI始终达到最先进水平，并进一步推进了感知-失真权衡的帕累托前沿。
原文摘要 · Abstract (English)
Diffusion bridges (DB) have emerged as a promising alternative to diffusion models for imaging inverse problems, achieving faster sampling by directly bridging low- and high-quality image distributions. While incorporating measurement consistency has been shown to improve performance, existing DB methods fail to maintain this consistency in blind inverse problems, where the forward model is unknown. To address this limitation, we introduce ADOBI (Adaptive Diffusion Bridge for Inverse Problems), a novel framework that adaptively calibrates the unknown forward model to enforce measurement consistency throughout sampling iterations. Our adaptation strategy allows ADOBI to achieve high-quality parallel magnetic resonance imaging (PMRI) reconstruction in only 5-10 steps. Our numerical results show that ADOBI consistently delivers state-of-the-art performance, and further advances the Pareto frontier for the perception-distortion trade-off.
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