Accurate estimation of the initial pressure distribution in photoacoustic computed tomography (PACT) depends on knowledge of the sound speed distribution. However, the sound speed distribution is typically unknown. Further, the initial pressure and sound speed distributions cannot both, in general, be stably recovered from PACT measurements alone. In this work, a joint reconstruction (JR) method for the initial pressure distribution and a low-dimensional parameterized model of the sound speed distribution is proposed. By employing a priori information about the structure of the sound speed distribution, both the initial pressure and sound speed can be accurately recovered. The JR problem is solved by use of a proximal optimization method that allows constraints and non-smooth regularization functions for the initial pressure distribution. The gradients of the cost function with respect to the initial pressure and sound speed distributions are calculated by use of an adjoint state method that has the same per-iteration computational cost as calculating the gradient with respect to the initial pressure distribution alone. This approach is evaluated through 2D computer-simulation studies for a small animal imaging model and by application to experimental in vivo measurements of a mouse.

中文翻译：

---

光声计算机断层扫描的初始压力和声速分布的参数化联合重建。


光声计算机断层扫描 (PACT) 中初始压力分布的准确估计取决于对声速分布的了解。然而，声速分布通常是未知的。此外，一般来说，初始压力和声速分布不能仅从 PACT 测量中稳定地恢复。在这项工作中，提出了一种初始压力分布的联合重建（JR）方法和声速分布的低维参数化模型。通过利用有关声速分布结构的先验信息，可以准确地恢复初始压力和声速。 JR 问题通过使用近端优化方法来解决，该方法允许初始压力分布的约束和非平滑正则化函数。成本函数相对于初始压力和声速分布的梯度是通过使用伴随状态方法来计算的，该方法具有与单独计算相对于初始压力分布的梯度相同的每次迭代计算成本。通过对小动物成像模型进行 2D 计算机模拟研究以及应用于小鼠体内实验测量来评估该方法。