Han Yiyong, Ding Lu, Ben Xosé Luis Deán, Razansky Daniel, Prakash Jaya, Ntziachristos Vasilis
Opt Lett. 2017 Mar 1;42(5):979-982. doi: 10.1364/OL.42.000979.
Optoacoustic tomography based on insufficient spatial sampling of ultrasound waves leads to loss of contrast and artifacts on the reconstructed images. Compared to reconstructions based on L2-norm regularization, sparsity-based reconstructions may improve contrast and reduce image artifacts but at a high computational cost, which has so far limited their use to 2D optoacoustic tomography. Here we propose a fast, sparsity-based reconstruction algorithm for 3D optoacoustic tomography, based on gradient descent with Barzilai-Borwein line search (L1-GDBB). Using simulations and experiments, we show that the L1-GDBB offers fourfold faster reconstruction than the previously reported L1-norm regularized reconstruction based on gradient descent with backtracking line search. Moreover, the new algorithm provides higher-quality images with fewer artifacts than the L2-norm regularized reconstruction and the back-projection reconstruction.
基于超声波空间采样不足的光声断层扫描会导致重建图像上的对比度损失和伪影。与基于L2范数正则化的重建相比，基于稀疏性的重建可能会改善对比度并减少图像伪影，但计算成本很高，到目前为止，这限制了它们仅用于二维光声断层扫描。在此，我们提出一种用于三维光声断层扫描的基于稀疏性的快速重建算法，该算法基于带有Barzilai-Borwein线搜索的梯度下降（L1-GDBB）。通过模拟和实验，我们表明L1-GDBB的重建速度比先前报道的基于带有回溯线搜索的梯度下降的L1范数正则化重建快四倍。此外，与L2范数正则化重建和反投影重建相比，新算法提供了质量更高、伪影更少的图像。
