迭代重建
计算机科学
投影(关系代数)
外推法
重建算法
计算机视觉
过程(计算)
加速
地震偏移
算法
人工智能
数学
地质学
操作系统
数学分析
地震学
作者
Haoran Jin,Zesheng Zheng,Shuangli Liu,Ruochong Zhang,Xinqin Liao,Siyu Liu,Yuanjin Zheng
出处
期刊:IEEE transactions on computational imaging
日期:2020-01-01
卷期号:6: 1097-1105
被引量:11
标识
DOI:10.1109/tci.2020.3005479
摘要
In recent years, photoacoustic image reconstruction has received extensive attention. Various reconstruction methods, such as back-projection, frequency domain reconstruction, time reversal, and model-based reconstructions have been developed. Although these methods are based on different propagation theories, they have relatively simple implementations when reconstructing images on homogenous media. However, in cases of heterogeneous layered media, like photoacoustic transcranial imaging, the propagation models have to be modified to accommodate various acoustic effects at layer interface, which complicates the reconstruction process. In this article, we propose an algorithm extension called pre-migration to first convert the reconstruction problems that apply to homogeneous media. From there, the sources can be rebuilt again using classical reconstruction methods. Pre-migration does not require classical reconstructions to be modified. It only preadjusts the sensor position via wave extrapolation. It also simplifies a focused transducer model as a point-like sensor. Based on simulation and experiment results, pre-migration can be integrated into almost all classical reconstruction algorithms and successfully solves reconstruction problems when imaging through heterogeneous media. In our experiments, it takes less than 20% of the total computational time during the entire reconstruction process.
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