用瑞托近似改进超声波反演,提升骨骼肌组织成像精度。
Hybrid Full Waveform Inversion Assisted by Rytov Approximation for Musculoskeletal Ultrasound Computed Tomography

- 结合瑞托近似与全波形反演,改善初始模型依赖性。
- 在有限带宽下实现接近理想初始模型的成像效果。
- 无需额外计算成本,适合实时临床应用。
超声计算机断层成像正成为一种安全且可及的软组织医学成像新方式,全波形反演在实现高分辨率、定量重建方面起关键作用。针对频率域全波形反演(FDFWI)在肌肉骨骼系统中对低频信号质量高度敏感的问题,本文提出一种混合全波形反演(HFWI)算法,将基于广义瑞托近似(generalized Rytov approximation)的走时反演方法嵌入到FDFWI框架中。该策略显著提升了早期反演质量,大幅降低对初始模型的敏感性,同时保持计算效率。重要的是,HFWI在无需优质初始模型的情况下,实现了与精心构造初始模型相当的成像结果,且无额外计算开销,可在真实带宽受限条件下实现精确成像。此外,提出一种近实时更新初至走时的方法,仅利用前向散射相位变化,无需额外波场模拟。数值模拟及体外、体内实验验证了该方法的鲁棒性与高效性。HFWI还展现出向更复杂肌肉骨骼参数重建场景扩展的潜力。
原文摘要 · Abstract (English)
Ultrasound computed tomography is emerging as a promising safe and accessible modality for soft-tissue medical imaging, with full waveform inversion playing a key role in unlocking its full potential for high-resolution, quantitative reconstructions. Frequency domain full waveform inversion (FDFWI) for reconstructing spatial maps of acoustic properties in the musculoskeletal system is highly sensitive to the quality of low-frequency signals, making the final imaging outcome vulnerable to issues such as inappropriate initial models and strong scatterings related to bones. To address these challenges, we propose a hybrid full waveform inversion (HFWI) algorithm that incorporates a traveltime inversion algorithm based on the generalized Rytov approximation into the FDFWI framework. This hybrid strategy enhances early-stage inversion quality and substantially reduces sensitivity to the initial model, all while maintaining computational efficiency. Importantly, HFWI achieves results comparable to those obtained using well-constructed initial models, without incurring extra computational cost, thus enabling accurate imaging under realistic, bandwidth-limited conditions. In addition, we introduce a near real-time strategy to update first-arrival traveltimes based on forward-scattered phase variations without requiring extra wavefield simulations. Numerical simulations, as well as \textit{in vitro} and \textit{in vivo} experiments confirm the robustness and efficiency of the proposed approach. HFWI also shows promise to extend to more complex scenarios of musculoskeletal parametric reconstruction.
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