RESEARCH ARTICLE

Laser speckle contrast imaging with principal component and entropy analysis: a novel approach for depth-independent blood flow assessment  

Yu. Surkov, P. Timoshina, I. Serebryakova, D. Stavtcev, I. Kozlov, G. Piavchenko, I. Meglinski, A. Konovalov, D. Telyshev, S. Kuznetcov, E. Genina, V. Tuchin

2025, 18(1): 1.https://doi.org/10.1007/s12200-024-00143-1

Abstract：Current study presents an advanced method for improving the visualization of subsurface blood vessels using laser speckle contrast imaging (LSCI), enhanced through principal component analysis (PCA) filtering. By combining LSCI and laser speckle entropy imaging with PCA filtering, the method effectively separates static and dynamic components of the speckle signal, significantly improving the accuracy of blood flow assessments, even in the presence of static scattering layers located above and below the vessel. Experiments conducted on optical phantoms, with the vessel depths ranging from 0.6 to 2 mm, and in vivo studies on a laboratory mouse ear demonstrate substantial improvements in image contrast and resolution. The method’s sensitivity to blood flow velocity within the physiologic range (0.98-19.66 mm/s) is significantly enhanced, while its sensitivity to vessel depth is minimized. These results highlight the method’s ability to assess blood flow velocity independently of vessel depth, overcoming a major limitation of conventional LSCI techniques. The proposed approach holds great potential for non-invasive biomedical imaging, offering improved diagnostic accuracy and contrast in vascular imaging. These findings may be particularly valuable for advancing the use of LSCI in clinical diagnostics and biomedical research, where high precision in blood flow monitoring is essential.

研究背景

激光散斑对比成像（LSCI）是一种基于散斑模式分析的光学成像技术，广泛应用于血管和组织灌注成像。然而，传统LSCI技术在处理深层血管时存在局限性，因为静态散射层（如皮肤表层或颅骨）会干扰信号，降低成像对比度和分辨率。

主要内容

本研究提出了一种结合主成分分析（PCA）和熵分析的新型LSCI方法，用于深度独立的血流评估。通过结合LSCI和激光散斑熵成像（LASEI）并应用PCA过滤，该方法能够有效分离静态和动态散斑信号成分，显著提高血流评估的准确性。

创新点

· 提出了一种深度独立的血流评估方法，克服了传统LSCI技术对血管深度的敏感性。

· 结合PCA过滤和熵分析，显著提高了成像对比度和分辨率。

· 在光学仿体和活体小鼠耳实验中验证了该方法的有效性。

方法

· 实验设计：使用光学仿体模拟不同深度的血管（0.6-2 mm），并通过活体小鼠耳实验验证方法的有效性。

· 成像技术：结合了LSCI、LASEI和PCA过滤，分离静态和动态散斑信号。

· 数据分析：通过计算散斑对比度和熵值，评估不同深度和流速下的成像效果。

结果

· 在光学仿体实验中，该方法显著提高了图像对比度和分辨率，尤其是在深层血管成像中。

· 在活体小鼠耳实验中，经过PCA过滤后的图像更清晰，血管背景噪声显著降低。

· 对于生理范围内的血流速度（0.98-19.66 mm/s），该方法的敏感性显著提高，且对血管深度的依赖性最小化。

总结

这项研究为非侵入性生物医学成像提供了新的技术手段，有望在临床诊断和生物医学研究中实现更精确的血流监测。通过提高成像精度和对比度，该方法为血管成像领域带来了新的突破！

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