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Iterative algorithm for multiple illumination photoacoustic tomography (MIPAT) using ultrasound channel data

机译:使用超声通道数据的多照明光声层析成像(MIPAT)的迭代算法

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摘要

Photoacoustic tomography is a promising imaging modality offering high ultrasonic resolution with intrinsic optical contrast. However, quantification in photoacoustic imaging is challenging. We present an algorithm for quantitative photoacoustic estimation of optical absorption and diffusion coefficients based on minimizing an error function between measured photoacoustic channel data and a calculated forward model with a multiple-illumination pattern. Unlike many other algorithms, the proposed method does not require the erroneous assumption of ideal tomographic reconstruction of initial pressures and to our knowledge is the first demonstration of the efficacy of multiple-illumination photoacoustic tomography requiring only transducer channel data. Simulations show promise for numerically robust optical property estimation as illustrated by well-conditioned Hessian singular values in 2D examples.
机译:光声层析成像是一种有前途的成像方式,可提供具有固有光学对比度的高超声分辨率。但是,光声成像中的量化具有挑战性。我们提出了一种基于最小化测得的光声通道数据与具有多个照明模式的正向模型之间的误差函数的,用于光学吸收和扩散系数的定量光声估计的算法。与许多其他算法不同,所提出的方法不需要错误地假设初始压力应进行理想的层析成像重建,并且据我们所知,这是仅需要换能器通道数据的多照明光声层析成像功效的首次证明。仿真表明,如2D实例中条件良好的Hessian奇异值所示,其数值鲁棒的光学性能估计具有希望。

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