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Time-domain reconstruction algorithms and numerical simulations for thermoacoustic tomography in various geometries

机译:各种几何形状的热声层析成像的时域重建算法和数值模拟

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摘要

In this paper, we present time-domain reconstruction algorithms for the thermoacoustic imaging of biological tissues. The algorithm for a spherical measurement configuration has recently been reported in another paper. Here, we extend the reconstruction algorithms to planar and cylindrical measurement configurations. First, we generalize the rigorous reconstruction formulas by employing Green's function technique. Then, in order to detect small (compared with the measurement geometry) but deeply buried objects, we can simplify the formulas when two practical conditions exist: 1) that the high-frequency components of the thermoacoustic signals contribute more to the spatial resolution than the low-frequency ones, and 2) that the detecting distances between the thermoacoustic sources and the detecting transducers are much greater than the wavelengths of the high-frequency thermoacoustic signals (i.e., those that are useful for imaging). The simplified formulas are computed with temporal back projections and coherent summations over spherical surfaces using certain spatial weighting factors. We refer to these reconstruction formulas as modified back projections. Numerical results are given to illustrate the validity of these algorithms.
机译:在本文中,我们提出了用于生物组织热声成像的时域重建算法。最近在另一篇论文中报道了用于球形测量配置的算法。在这里,我们将重建算法扩展到平面和圆柱测量配置。首先,我们采用格林函数技术对严格的重构公式进行概括。然后,为了检测较小的(与测量几何体相比)但深埋的物体,当存在两个实际条件时,我们可以简化公式:1)热声信号的高频分量对空间分辨率的贡献要大于对高频的贡献。 2)热声源和检测换能器之间的检测距离远大于高频热声信号的波长(即对成像有用的波长)。使用某些空间权重因子,通过球面曲面上的时间反投影和相干求和来计算简化公式。我们将这些重建公式称为修改后的投影。数值结果表明了这些算法的有效性。

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