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Constrained Inversion and Spectral Unmixing in Multispectral Optoacoustic Tomography

机译:多光谱光声层析成像中的约束反演和光谱解混

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摘要

Accurate extraction of physical and biochemical parameters from optoacoustic images is often impeded due to the use of unrigorous inversion schemes, incomplete tomographic detection coverage, or other experimental factors that cannot be readily accounted for during the image acquisition and reconstruction process. For instance, inaccurate assumptions in the physical forward model may lead to negative optical absorption values in the reconstructed images. Any artifacts present in the single wavelength optoacoustic images can be significantly aggravated when performing a two-step reconstruction consisting in acoustic inversion and spectral unmixing aimed at rendering the distributions of spectrally distinct absorbers. We investigate a number of algorithmic strategies with non-negativity constraints imposed at the different phases of the reconstruction process. Performance is evaluated in cross-sectional multispectral optoacoustic tomography recordings from tissue-mimicking phantoms and in vivo mice embedded with varying concentrations of contrast agents. Additional in vivo validation is subsequently performed with molecular imaging data involving subcutaneous tumors labeled with genetically expressed iRFP proteins and organ perfusion by optical contrast agents. It is shown that constrained reconstruction is essential for reducing the critical image artifacts associated with inaccurate modeling assumptions. Furthermore, imposing the non-negativity constraint directly on the unmixed distribution of the probe of interest was found to maintain the most robust and accurate reconstruction performance in all experiments.
机译:由于使用了不严格的反演方案,不完整的层析成像检测覆盖率或在图像采集和重建过程中无法轻易解释的其他实验因素,通常会妨碍从光声图像中准确提取物理和生化参数。例如,物理正向模型中的不正确假设可能导致重建图像中的光吸收值为负。当执行两步重建(包括声学反演和频谱解混)时,可以显着加剧单波长光声图像中存在的任何伪影,目的在于渲染光谱上不同的吸收体。我们研究了在重建过程的不同阶段施加非负约束的多种算法策略。在横截面的多光谱光声层析成像记录中评估了性能,这些记录来自模仿组织的体模和嵌入了不同浓度造影剂的体内小鼠。随后,利用涉及以遗传表达的iRFP蛋白标记的皮下肿瘤以及通过光学造影剂进行器官灌注的分子成像数据,进行额外的体内验证。结果表明,约束重构对于减少与不正确的建模假设相关的关键图像伪影至关重要。此外,发现将非负性约束直接施加在目标探针的未混合分布上可以在所有实验中保持最稳定,最准确的重建性能。

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