Institute for Biological and Medical Imaging, Technical University of Munich and Helmholtz Center Munich, Neuherberg 85764, Germany.
Sensors (Basel). 2013 Jun 4;13(6):7345-84. doi: 10.3390/s130607345.
This paper comprehensively reviews the emerging topic of optoacoustic imaging from the image reconstruction and quantification perspective. Optoacoustic imaging combines highly attractive features, including rich contrast and high versatility in sensing diverse biological targets, excellent spatial resolution not compromised by light scattering, and relatively low cost of implementation. Yet, living objects present a complex target for optoacoustic imaging due to the presence of a highly heterogeneous tissue background in the form of strong spatial variations of scattering and absorption. Extracting quantified information on the actual distribution of tissue chromophores and other biomarkers constitutes therefore a challenging problem. Image quantification is further compromised by some frequently-used approximated inversion formulae. In this review, the currently available optoacoustic image reconstruction and quantification approaches are assessed, including back-projection and model-based inversion algorithms, sparse signal representation, wavelet-based approaches, methods for reduction of acoustic artifacts as well as multi-spectral methods for visualization of tissue bio-markers. Applicability of the different methodologies is further analyzed in the context of real-life performance in small animal and clinical in-vivo imaging scenarios.
本文从图像重建和量化的角度全面综述了光声成像这一新兴课题。光声成像是一种极具吸引力的技术，它在探测多种生物靶标时具有丰富的对比度和多功能性、对光散射不敏感的优异空间分辨率，以及相对较低的实现成本。然而，由于组织背景存在强烈的散射和吸收空间变化，活体对象对光声成像来说是一个复杂的目标。因此，提取关于组织色团和其他生物标志物实际分布的量化信息是一个具有挑战性的问题。图像量化进一步受到一些常用的近似反演公式的影响。在本文中，评估了现有的光声图像重建和量化方法，包括反向投影和基于模型的反演算法、稀疏信号表示、基于小波的方法、减少声伪影的方法以及用于可视化组织生物标志物的多光谱方法。进一步在小动物和临床体内成像场景的实际性能背景下分析了不同方法的适用性。
