物理指导的深度展开全波形反演用于水肿检测
Physics Informed Deep Unfolded Full Waveform Inversion for Edema Detection
AI总结：
本文提出深度展开全波形反演方法，用于实时检测水肿，通过学习更新规则提升重建效率和精度。
摘要：
水肿是潜在病理变化的指标。然而，其低对比度特征往往在传统B模成像中被强散射体掩盖，使可靠检测变得困难。超声（US）提供了一种非侵入性、非电离性和成本效益高的成像选择，被广泛使用。传统技术依赖于波束成形，通常缺乏足够的物理可解释性。定量超声（QUS）可以通过在测量的超声波场上直接求解基于物理的反问题来估计物理属性，如声速（SoS）和密度，即恢复其空间分布。然而，最先进的基于物理的反演方法，包括全波形反演（FWI）和基于模型的定量雷达和超声（MB-QRUS），计算上耗费资源且容易陷入局部极小值，这限制了其临床应用。我们引入了深度展开FWI（DUFWI），一种物理忠实的展开迭代反演方法，它表现出FWI类似的细化行为，同时从数据中学习更新规则，仅需少量迭代即可实现实时SoS重建。在模拟数据集和使用Verasonics超声系统获取的硬件测量中，DUFWI在重建质量上显著优于传统FWI和MB-QRUS，同时保持高计算效率。这些结果在模拟和硬件实验中展示了实时水肿诊断，通过使用圆柱形杆的假体验证，支持在典型超声成像设置下实际部署。
英文摘要：
Edema is a potential indicator of underlying pathological changes. However, its low-contrast signature is often masked in conventional B-mode imaging by strong scatterers, making reliable detection challenging. Ultrasound (US) provides a non-invasive, non-ionizing, and cost-efficient imaging option that is widely used. Conventional techniques, which rely on beamforming, often lack sufficient physical interpretability. Quantitative US (QUS) can estimate physical properties such as the speed of sound (SoS) and density by solving a physics-based inverse problem directly on the measured US wavefields, i.e., the raw per-element channel data (CD), to recover their spatial distribution. However, state-of-the-art physics-based inversion methods, including full waveform inversion (FWI) and model-based quantitative radar and US (MB-QRUS), are computationally intensive and susceptible to local minima, which constrains their clinical utility. We introduce deep unfolded FWI (DUFWI), a physics-faithful unfolded iterative inversion method that exhibits FWI-like refinement behavior while learning the update rule from data, requiring only a small number of iterations for real-time SoS reconstruction. Across both simulated datasets and hardware measurements acquired with a Verasonics US system, the DUFWI significantly outperforms classical FWI and MB-QRUS in reconstruction quality while maintaining high computational efficiency. These results demonstrate real-time edema diagnosis in both simulation and hardware experiments, with phantom-based validation using cylindrical rods, supporting practical deployment under typical US imaging setting.
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