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Three-Dimensional Microwave-Induced Thermoacoustic Imaging Based on Compressive Sensing Using an Analytically Constructed Dictionary

机译:基于解析构造字典的基于压缩感测的三维微波热声成像

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Microwave-induced thermoacoustic imaging (MITAI) has found diversified applications in biomedical related disciplines and holds the potential to serve as an auxiliary measure for diagnosis and treatment in clinics. Conventional imaging algorithms for MITAI, for example, back-projection (BP), require exceedingly intensive sampling of thermoacoustic signals stemming from a sample under test, and thus, suffer from deficiencies such as low time efficiency, high system cost, and more microwave radiation received by patients. Combining compressive sensing (CS) and MITAI, referred to as CS-MITAI, is promising to address the problem. Reported experiments in two dimensions and simulations in three dimensions (3D) have proved that the CS-MITAI approach can reliably reconstruct images with much fewer measurements than the BP algorithm. However, there is a pressing need for the experimental validation of the CS-MITAI technique in a real three-dimensional (3-D) environment, which has profound implications for its practical applications and further improvement. This article experimentally investigates the 3-D CS-MITAI technique by imaging a sample with 3-D features. Establishment of a dictionary is crucial for the successful implementation of the 3-D CS-MITAI approach. An analytical method is proposed to build the dictionary with much higher efficiency than other reported measures, and its detailed derivation is provided. In addition, modeling work and parametric studies are performed to explore the robustness of the 3-D CS-MITAI mechanism in dealing with different cases. Both simulation and experimental results show that the 3-D CS-MITAI modality can offer comparable imaging quality as the BP method but requires 200 and 68 times fewer measurements, respectively.
机译:微波感应热声成像(MITAI)在生物医学相关学科中发现了多种应用,并有潜力作为临床诊断和治疗的辅助手段。用于MITAI的常规成像算法,例如反投影(BP),需要对来自被测样品的热声信号进行非常密集的采样,因此存在时间效率低,系统成本高以及更多微波辐射等缺陷被患者接受。将压缩感测(CS)和MITAI结合使用,称为CS-MITAI,有望解决这个问题。报告的二维实验和三维模拟(3D)已证明,与BP算法相比,CS-MITAI方法能够以更少的测量值可靠地重建图像。但是,迫切需要在真实的三维(3-D)环境中对CS-MITAI技术进行实验验证,这对其实际应用和进一步改进具有深远的意义。本文通过对具有3-D特征的样本进行成像,实验性地研究了3-D CS-MITAI技术。建立字典对于成功实施3-D CS-MITAI方法至关重要。提出了一种分析方法来建立比其他报告措施效率更高的字典,并提供了详细的推导方法。此外,还进行了建模工作和参数研究,以探索3-D CS-MITAI机制在处理不同情况时的鲁棒性。仿真和实验结果均表明,3-D CS-MITAI模态可提供与BP方法相当的成像质量,但分别需要少200倍和68倍的测量。

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