Three-dimensional photoacoustic imaging by sparsearray detection and iterative image reconstruction

Photoacoustic imaging (PAI) has the potential to acquire 3-D optical images at high speed. Attempts at 3-D photoacoustic imaging have used a dense 2-D array of ultrasound detectors or have densely scanned a single detector on a 2-D surface. The former approach is costly and complicated to realize, while the latter is inherently slow. We present a different approach based on a sparse 2-D array of detector elements and an iterative reconstruction algorithm. This approach has the potential for fast image acquisition, since no mechanical scanning is required, and for simple and compact construction due to the smaller number of detector elements. We obtained spatial sensitivity maps of the sparse array and used them to optimize the image reconstruction algorithm. We then validated the method on phantoms containing 3-D distributions of optically absorbing point sources. Reconstruction of the point sources from the time-domain signals resulted in images with good contrast and accurate localization (

光声成像（PAI）有可能高速获取三维光学图像。三维光声成像的尝试使用了密集的二维超声探测器阵列，或者在二维表面上密集扫描单个探测器。前一种方法成本高昂且实现复杂，而后一种方法本质上速度较慢。我们提出了一种基于探测器元件稀疏二维阵列和迭代重建算法的不同方法。这种方法由于不需要机械扫描而有可能实现快速图像采集，并且由于探测器元件数量较少而具有简单紧凑的结构。我们获得了稀疏阵列的空间灵敏度图，并利用它们优化图像重建算法。然后我们在含有光吸收点源三维分布的仿体上验证了该方法。从时域信号重建点源得到了具有良好对比度和准确定位的图像。