Significance: As linear array transducers are widely used in clinical ultrasound imaging, photoacoustic tomography (PAT) with linear arrays is similarly suitable for clinical applications. However, due to the limited-view problem, a linear array has limited performance and leads to artifacts and blurring, which has hindered its broader application. There is a need to address the limited-view problem in PAT imaging with linear arrays. Aim: We investigate potential approaches for improving PAT reconstruction from linear array, by optimizing the detection geometry and implementing iterative reconstruction. Approach: PAT imaging with a single-array, dual-probe configurations in parallel-shape and L-shape, and square-shape configuration are compared in simulations and phantom experiments. An iterative model-based algorithm based on the variance-reduced stochastic gradient descent (VR-SGD) method is implemented. The optimum configuration found in simulation is validated on phantom experiments. Results: PAT imaging with dual-probe detection and VR-SGD algorithm is found to improve the limited-view problem compared to a single probe and provide comparable performance as full-view geometry in simulation. This configuration is validated in experiments where more complete structure is obtained with reduced artifacts compared with a single array. Conclusions: PAT with dual-probe detection and iterative reconstruction is a promising solution to the limited-view problem of linear arrays.

中文翻译：

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线阵有限​​视野光声断层扫描重建研究

意义：由于线阵换能器广泛应用于临床超声成像，线阵光声断层扫描（PAT）同样适用于临床应用。然而，由于有限视角问题，线性阵列的性能有限，并导致伪影和模糊，阻碍了其更广泛的应用。需要解决线性阵列 PAT 成像中的视野受限问题。目的：我们通过优化检测几何结构和实施迭代重建来研究改善线性阵列 PAT 重建的潜在方法。方法：在模拟和体模实验中比较了具有平行形状和 L 形和方形配置的单阵列、双探头配置的 PAT 成像。实现了基于方差减少的随机梯度下降 (VR-SGD) 方法的基于迭代模型的算法。在仿真中找到的最佳配置在体模实验中得到验证。结果：发现使用双探针检测和 VR-SGD 算法的 PAT 成像与单探针相比改善了有限视野问题，并在模拟中提供了与全视野几何体相当的性能。这种配置在实验中得到了验证，与单个阵列相比，在减少伪影的情况下获得了更完整的结构。结论：具有双探针检测和迭代重建的 PAT 是解决线性阵列有限视角问题的有前途的解决方案。与单探头相比，使用双探头检测和 VR-SGD 算法的 PAT 成像可以改善有限视角问题，并在模拟中提供与全视角几何相当的性能。这种配置在实验中得到了验证，与单个阵列相比，在减少伪影的情况下获得了更完整的结构。结论：具有双探针检测和迭代重建的 PAT 是解决线性阵列有限视角问题的有前途的解决方案。与单探头相比，使用双探头检测和 VR-SGD 算法的 PAT 成像可以改善有限视角问题，并在模拟中提供与全视角几何相当的性能。这种配置在实验中得到了验证，与单个阵列相比，在减少伪影的情况下获得了更完整的结构。结论：具有双探针检测和迭代重建的 PAT 是解决线性阵列有限视角问题的有前途的解决方案。