College of Science, Hohai University, Nanjing 210098, Jiangsu, People's Republic of China.
Phys Med Biol. 2019 Sep 23;64(19):195004. doi: 10.1088/1361-6560/ab3704.
Photoacoustic tomography (PAT) is an emerging and effective imaging technique, which offers high spatial resolution with high contrast. In particular, the acquired data is incomplete due to geometrical limitations or accelerating data acquisition by undersampling technology, thus some artifacts will be presented in the reconstructed image. To deal with limited-view PAT, we introduce a [Formula: see text] regularization scheme into PAT and propose a three-stage method. We first use the gradient descent method to obtain an initial solution, then project it onto a constrain set, and finally a proximal mapping scheme is used to further improve the reconstruction quality. Our simulation experiments on homogeneous medium are utilized to validate the effectiveness of the proposed method, and a discussion on the parameters of the proposed method is given. The experimental results reveal that the proposed method outperforms other classical methods, and it can further improve the reconstruction quality in terms of suppressing the noise and artifacts, and preserving the edge.
光声断层成像（PAT）是一种新兴的有效成像技术，具有高空间分辨率和高对比度。特别是，由于几何限制或通过欠采样技术加速数据采集，获取的数据是不完整的，因此在重建图像中会出现一些伪影。为了解决有限视角的 PAT 问题，我们将 [Formula: see text] 正则化方案引入到 PAT 中，并提出了一种三阶段方法。我们首先使用梯度下降法得到一个初始解，然后将其投影到约束集上，最后使用一个邻近映射方案来进一步提高重建质量。我们在均匀介质上的仿真实验验证了所提出方法的有效性，并对该方法的参数进行了讨论。实验结果表明，该方法优于其他经典方法，可以进一步提高重建质量，在抑制噪声和伪影以及保持边缘方面都有较好的表现。
