用相位级不确定性引导重建，提升MRI参数图精度
Guiding Quantitative MRI Reconstruction with Phase-wise Uncertainty
- 分阶段重建中估计各相位不确定性
- 不确定性信息显著提升T1/T2映射准确率
- 适合需要高精度定量MRI的临床研究者
定量磁共振成像（qMRI）需多相采集，常依赖欠采样和重建算法加速扫描，导致病态逆问题。尽管已有研究关注过程中的不确定性度量，但极少探索如何利用它提升重建性能。本文提出PUQ，首次将不确定性信息用于qMRI重建。PUQ采用两阶段重建与参数拟合框架，在重建阶段估算各相位不确定性，并在拟合阶段加以利用。该设计使不确定性反映不同相位的可靠性，指导参数拟合中的信息融合。我们在健康受试者的活体T1和T2映射数据集上评估了PUQ，结果表明其在参数映射上达到当前最优表现，验证了不确定性引导的有效性。代码已公开于https://anonymous.4open.science/r/PUQ-75B2/。
原文摘要 · Abstract (English)
Quantitative magnetic resonance imaging (qMRI) requires multi-phase acqui-sition, often relying on reduced data sampling and reconstruction algorithms to accelerate scans, which inherently poses an ill-posed inverse problem. While many studies focus on measuring uncertainty during this process, few explore how to leverage it to enhance reconstruction performance. In this paper, we in-troduce PUQ, a novel approach that pioneers the use of uncertainty infor-mation for qMRI reconstruction. PUQ employs a two-stage reconstruction and parameter fitting framework, where phase-wise uncertainty is estimated during reconstruction and utilized in the fitting stage. This design allows uncertainty to reflect the reliability of different phases and guide information integration during parameter fitting. We evaluated PUQ on in vivo T1 and T2 mapping datasets from healthy subjects. Compared to existing qMRI reconstruction methods, PUQ achieved the state-of-the-art performance in parameter map-pings, demonstrating the effectiveness of uncertainty guidance. Our code is available at https://anonymous.4open.science/r/PUQ-75B2/.
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