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基于坐标变换的光声断层成像计算高效正算子。

Computationally Efficient Forward Operator for Photoacoustic Tomography Based on Coordinate Transformations.

出版信息

IEEE Trans Ultrason Ferroelectr Freq Control. 2021 Jun;68(6):2172-2182. doi: 10.1109/TUFFC.2021.3060175. Epub 2021 May 25.

DOI:10.1109/TUFFC.2021.3060175
PMID:33600313
Abstract

Photoacoustic tomography (PAT) is an imaging modality that utilizes the photoacoustic effect. In PAT, a photoacoustic image is computed from measured data by modeling ultrasound propagation in the imaged domain and solving an inverse problem utilizing a discrete forward operator. However, in realistic measurement geometries with several ultrasound transducers and relatively large imaging volume, an explicit formation and use of the forward operator can be computationally prohibitively expensive. In this work, we propose a transformation-based approach for efficient modeling of photoacoustic signals and reconstruction of photoacoustic images. In the approach, the forward operator is constructed for a reference ultrasound transducer and expanded into a general measurement geometry using transformations that map the formulated forward operator in local coordinates to the global coordinates of the measurement geometry. The inverse problem is solved using a Bayesian framework. The approach is evaluated with numerical simulations and experimental data. The results show that the proposed approach produces accurate 3-D photoacoustic images with a significantly reduced computational cost both in memory requirements and time. In the studied cases, depending on the computational factors, such as discretization, over the 30-fold reduction in memory consumption was achieved without a reduction in image quality compared to a conventional approach.

摘要

光声断层扫描(PAT)是一种利用光声效应的成像方式。在 PAT 中,通过对成像域中超声传播进行建模并利用离散正向算子求解反问题,从测量数据中计算出光声图像。然而,在具有多个超声换能器和相对较大成像体积的实际测量几何形状中,显式形成和使用正向算子在计算上可能过于昂贵。在这项工作中,我们提出了一种基于变换的方法,用于高效建模光声信号和重建光声图像。在该方法中,正向算子是针对参考超声换能器构建的,并使用变换扩展到一般测量几何形状,该变换将局部坐标中的公式化正向算子映射到测量几何形状的全局坐标。反问题通过贝叶斯框架求解。该方法通过数值模拟和实验数据进行了评估。结果表明,所提出的方法在计算成本显著降低的情况下,无论是在内存需求还是时间方面,都能产生准确的 3D 光声图像。在所研究的情况下,根据计算因素(例如离散化),与传统方法相比,在不降低图像质量的情况下,内存消耗减少了 30 倍以上。

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