提出新方法提升光声成像空间聚焦模拟精度,改善图像质量。
A Method for Accurate Spatial Focusing Simulation via Numerical Integration and its Application in Optoacoustic Tomography
- 直接计算空间脉冲响应(SPR),避免传统SIR方法的数值误差。
- 采用自适应积分算法,误差可预设控制,精度显著优于现有方法。
- 适用于高精度光声成像重建,提升对比度并抑制噪声伪影,适合医学影像研究者。
超声换能器的空间灵敏度受其表面形状影响,准确模拟其空间特性对换能器设计与成像系统建模至关重要。在光声成像中,宽带换能器虽能利用信号丰富的频谱成分,但导致通用波动方程求解器的模拟耗时耗内存。为此,已有专门工具用于模拟由空间脉冲响应(SIR)描述的聚焦特性。然而,SIR计算复杂且需与光声吸收体产生的波形卷积以模拟系统响应,易引入数值误差,且误差不可预先控制。为此,本文提出直接计算所需波形与SIR的卷积,称为空间脉冲响应(SPR)。通过使用h-自适应立方积分算法,SPR可实现更高精度,且误差可通过容差参数控制。将高精度SPR模拟集成至基于模型的光声图像重建中,显著提升了图像对比度并减少了噪声伪影。精确的系统表征与模拟有助于提升成像性能,增强光声成像系统在临床应用中的价值。
原文摘要 · Abstract (English)
The spatial sensitivity of an ultrasound transducer, which strongly influences its suitability for different applications, depends on the shape of the transducer surface. Accurate simulation of these spatial effects is important for transducer characterization and design, and for system response modelling in imaging applications. In optoacoustic imaging, broadband transducers are used to capitalize on the rich frequency content of the signals, but their usage makes highly accurate simulations with general wave equation solvers prohibitively memory- and time-intensive. Therefore, specialized tools for simulating the isolated spatial focusing properties described by the spatial impulse response (SIR) have been developed. However, the challenging numerics of the SIR and the necessity to convolve the SIR with the wave shape generated by the optoacoustic absorber to simulate the system response lead to numerical inaccuracies of SIR-based methods. In addition, the approximation error of these methods cannot be controlled a priori. To circumvent the problems associated with the explicit calculation of SIR, we propose directly computing the convolution of the required wave shape with the SIR, which we call the spatial pulse response (SPR). We demonstrate that by utilizing an h-adaptive cubature algorithm, SPR can be computed with significantly higher accuracy than an SIR-based reference method, and the approximation error can be controlled with a tolerance parameter. In addition, the integration of accurate SPR simulations into model-based optoacoustic image reconstruction is shown to improve image contrast and reduce noise artifacts. Precise system characterization and simulation leads to improved imaging performance, ultimately increasing the value of optoacoustic imaging systems for clinical applications.
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