Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Neuherberg, Germany.
Chair of Biological Imaging at the Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Munich, Germany.
J Biophotonics. 2022 Jun;15(6):e202100334. doi: 10.1002/jbio.202100334. Epub 2022 Mar 6.
Acoustic heterogeneities in biological samples are known to cause artifacts in tomographic optoacoustic (photoacoustic) image reconstruction. A statistical weighted model-based reconstruction approach was previously introduced to mitigate such artifacts. However, this approach does not reliably provide high-quality reconstructions for partial-view imaging systems, which are common in preclinical and clinical optoacoustics. In this article, the capability of the weighted model-based algorithm is extended to generate optoacoustic reconstructions with less distortions for partial-view geometry data. This is achieved by manipulating the weighting scheme based on the detector geometry. Using partial-view optoacoustic tomography data from a tissue-mimicking phantom containing a strong acoustic reflector, tumors grafted onto mice, and a mouse brain with intact skull, the proposed partial-view-corrected weighted model-based algorithm is shown to mitigate reflection artifacts in reconstructed images without distorting structures or boundaries, compared with both conventional model-based and the weighted model-based algorithms. It is also demonstrated that the partial-view-corrected weighted model-based algorithm has the additional advantage of suppressing streaking artifacts due to the partial-view geometry itself in the presence of a very strong optoacoustic chromophore. Due to its enhanced performance, the partial-view-corrected weighted model-based algorithm may prove useful for improving the quality of partial-view multispectral optoacoustic tomography, leading to enhanced visualization of functional parameters such as tissue oxygenation.
生物样本中的声异质性已知会导致层析光声（光声）图像重建中的伪影。先前已经引入了一种基于统计加权模型的重建方法来减轻这种伪影。然而，对于部分视场成像系统，这种方法并不可靠，部分视场成像系统在临床前和临床光声中很常见。在本文中，加权模型算法的功能扩展到为部分视场几何数据生成失真较小的光声重建。这是通过基于探测器几何形状来操纵加权方案来实现的。使用包含强声反射器的组织模拟体模、移植到小鼠上的肿瘤以及具有完整颅骨的小鼠大脑的部分视场光声断层扫描数据，与传统的基于模型的算法和加权模型算法相比，所提出的部分视场校正加权模型算法被证明可以减轻重建图像中的反射伪影，而不会扭曲结构或边界。还证明了，在存在非常强的光声发色团的情况下，部分视场校正加权模型算法具有抑制由于部分视场几何形状本身引起的条纹伪影的额外优点。由于其增强的性能，部分视场校正加权模型算法可能有助于提高部分视场多光谱光声断层扫描的质量，从而增强对组织氧合等功能参数的可视化。
