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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Spatial Response Identification for Flexible and Accurate Ultrasound Transducer Calibration and its Application to Brain Imaging
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Spatial Response Identification for Flexible and Accurate Ultrasound Transducer Calibration and its Application to Brain Imaging

机译:灵活准确的超声换能器校准的空间响应识别及其在脑成像中的应用

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摘要

Accurate wave-equation modeling is becoming increasingly important in modern imaging and therapeutic ultrasound methodologies, such as ultrasound computed tomography, optoacoustic tomography, or high-intensity-focused ultrasound. All of them rely on the ability to accurately model the physics of wave propagation, including accurate characterization of the ultrasound transducers, the physical devices that are responsible for generating and recording ultrasound energy. However, existing methods fail to characterize the transducer response with the accuracy required to fully exploit the capabilities of these emerging imaging and therapeutic techniques. Consequently, we have designed a new algorithm for ultrasound transducer calibration and modeling: spatial response identification (SRI). This method introduces a parameterization of the ultrasound transducer and provides a method to calibrate the transducer model using experimental data, based on a formulation of the problem that is completely independent of the discretization chosen for the transducer or the number of parameters used. The proposed technique models the transducer as a linear time-invariant system that is spatially heterogeneous, and identifies the model parameters that are best at explaining the experimental data while honoring the full wave equation. SRI generates a model that can accommodate the complex, heterogeneous spatial response seen experimentally for ultrasound transducers. Experimental results show that SRI outperforms standard methods both in transmission and reception modes. Finally, numerical experiments using full-waveform inversion demonstrate that existing transducer-modeling approaches are insufficient to produce successful reconstructions of the human brain, whereas errors in our SRI algorithm are sufficiently small to allow accurate image reconstructions.
机译:精确的波浪方面建模在现代成像和治疗超声方法中变得越来越重要,例如超声波计算机断层扫描,光声断层扫描或高强度聚焦超声波。所有这些都依赖于准确地模拟波传播物理学的能力,包括精确表征超声换能器,该物理设备负责产生和记录超声能量。然而,现有方法未能表征传感器响应,以完全利用这些新兴成像和治疗技术的能力所需的准确性。因此,我们设计了一种新的超声换能器校准和建模算法:空间响应识别(SRI)。该方法引入超声换能器的参数化,并提供一种使用实验数据校准换能器模型的方法,基于完全独立于为换能器所选择的离散化或所用参数的参数的数量来校准换能器模型。所提出的技术模拟换能器作为空间异构的线性时间不变系统,并识别最佳的模型参数,该参数最适合在纪念全波方程时解释实验数据。 SRI生成一个模型,可以适应实验上看到的复杂的异构空间响应,用于超声换能器。实验结果表明,SRI在传输和接收模式下表现出标准方法。最后,使用全波形反演的数值实验表明,现有的传感器建模方法不足以产生人类大脑的成功重建,而我们的SRI算法中的错误足够小以允许准确的图像重建。

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