用扩散模型无损修正心脏SPECT图像的衰减伪影
PADM: A Physics-aware Diffusion Model for Attenuation Correction
- 基于物理先验的教师-学生蒸馏机制，实现无需CT的衰减校正
- 在424例患者数据上验证，重建质量优于现有生成模型
- 适合临床缺乏CT设备时提升SPECT诊断准确性
心肌灌注显像（MPI）中单光子发射计算机断层扫描（SPECT）的衰减伪影严重影响诊断准确性和临床可读性。尽管混合SPECT/CT系统可通过CT获取的衰减图缓解此问题，但其高昂成本、普及率低及额外辐射暴露限制了广泛应用。本文提出一种无需CT的衰减校正新方案：物理感知衰减校正扩散模型（PADM），该模型通过教师-学生蒸馏机制引入显式物理先验，在仅使用非衰减校正（NAC）输入的情况下仍能获得物理一致的校正结果。为支持研究，我们构建了包含424例患者研究的CardiAC数据集，含配对的NAC与衰减校正（AC）重建图像以及高分辨率CT衰减图。大量实验表明，PADM在定量指标和视觉评估上均超越当前最优生成模型，显著提升重建保真度。
原文摘要 · Abstract (English)
Attenuation artifacts remain a significant challenge in cardiac Myocardial Perfusion Imaging (MPI) using Single-Photon Emission Computed Tomography (SPECT), often compromising diagnostic accuracy and reducing clinical interpretability. While hybrid SPECT/CT systems mitigate these artifacts through CT-derived attenuation maps, their high cost, limited accessibility, and added radiation exposure hinder widespread clinical adoption. In this study, we propose a novel CT-free solution to attenuation correction in cardiac SPECT. Specifically, we introduce Physics-aware Attenuation Correction Diffusion Model (PADM), a diffusion-based generative method that incorporates explicit physics priors via a teacher--student distillation mechanism. This approach enables attenuation artifact correction using only Non-Attenuation-Corrected (NAC) input, while still benefiting from physics-informed supervision during training. To support this work, we also introduce CardiAC, a comprehensive dataset comprising 424 patient studies with paired NAC and Attenuation-Corrected (AC) reconstructions, alongside high-resolution CT-based attenuation maps. Extensive experiments demonstrate that PADM outperforms state-of-the-art generative models, delivering superior reconstruction fidelity across both quantitative metrics and visual assessment.
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