Sub-micron weak phase particle characterization using the reconstructed volume intensities from in-line digital holography microscopy
Sub-micron weak phase particle characterization using the reconstructed volume intensities from in-line digital holography microscopy
复制标题
使用在线数字全息显微镜重建体积强度进行亚微米弱相粒子表征
DOI：
10.1016/j.optlaseng.2023.107779
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发表时间：
2023
影响因子：
4.6
通讯作者：
Ardekani, Arezoo M.
中科院分区：
文献类型：
--
作者：
Barrio-Zhang, Andres;Ardekani, Arezoo M.
数字全息显微镜是一种强大的技术，用于检索通常难以通过其他方法获得的粒子特性。然而，如果没有先验信息，使用非线性拟合算法和机器学习来分析全息数据是很困难的。在本文中，我们提出了一种利用瑞利-索末菲衍射理论来确定亚微米弱相球形颗粒的尺寸和折射率的新技术。我们的方法涉及使用 HoloPy 软件针对不同尺寸和材料特性的粒子重建合成全息图的体积。然后，我们在数值重新聚焦点处拟合高斯函数，如古伊相移后的第一个局部最小值给出的那样，用于大小和子像素位置估计。通过检索最大散射强度的幅度和位置，我们构建了一个与所有感兴趣参数相关的散射插值。我们证明，我们的技术与合成数据相比，颗粒折射率的平均误差为 1.24 ± 1.74%，并在实验中准确估计了类似尺寸纳米颗粒的尺寸和折射率。与最小二乘拟合相比，我们的方法在合成数据上的表现相似，但在实验数据上的表现优于它，展示了其卓越的准确性和可靠性。此外，我们将我们的技术与功能拟合方法相结合。这种混合方法使用我们提出的技术来近似非线性拟合算法的初始条件，从而提高了精度。最后，我们探索了使用强度立方体作为明确定义的阈值来区分重建体积中的粒子与干扰焦散的潜力。总的来说，我们的结果证明了我们的技术从全息数据检索粒子属性的有效性和准确性，即使在先前信息不可用的情况下也是如此。该技术在纳米颗粒表征领域具有广泛的应用。
Digital holography microscopy is a powerful technique for retrieving particle properties that are often challenging to obtain with other methods. However, analyzing holographic data using non-linear fitting algorithms and machine learning is difficult without prior information. In this paper, we present a novel technique for sizing and determining the refractive index of sub-micron, weak phase, spherical particles using the Rayleigh-Sommerfeld diffraction theory. Our method involves reconstructing the volume of synthetic holograms using the HoloPy software for particles of different sizes and material properties. We then fit a Gaussian function at the point of numerical re-focus, as given by the first local minima after the Gouy-phase shift, for size and sub-pixel position estimates. By retrieving the magnitude and location of the maximum scattered intensity, we build a scattered interpolant that relates all the parameters of interest. We demonstrate that our technique had a mean error in particle refractive index of 1.24 ± 1.74% with synthetic data and accurately estimates the size and refractive index of similar-sized nanoparticles in experiments. Compared to least-squares fitting, our method performs similarly with synthetic data but outperformed it with experimental data, showcasing its superior accuracy and reliability. Furthermore, we use our technique combined with function-fitting approaches. This hybrid method uses our proposed technique to approximate the initial conditions of non-linear fitting algorithms, leading to improved accuracy. Finally, we explore the potential of using the intensity cubes as well-defined thresholds to differentiate particles from interference caustics in a reconstructed volume. Overall, our results demonstrate the efficacy and accuracy of our technique for retrieving particle properties from holographic data, even when prior information was not available. This technique could have broad applications in the field of nanoparticle characterization.
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影响因子：
3.8
作者：
Latychevskaia, Tatiana;Fink, Hans-Werner
通讯作者：
Fink, Hans-Werner
影响因子：
2.1
作者：
Barkley, Solomon;Dimiduk, Thomas G.;Wang, Anna
通讯作者：
Wang, Anna
影响因子：
4
作者：
Cheong, Fook Chiong;Kasimbeg, Priya;Grier, David G.
通讯作者：
Grier, David G.
使用光散射图案的相位谱检索单个球体的折射率
DOI：
--
发表时间：
2022
期刊：
Optics & Laser Technology
影响因子：
--
作者：
A. Romanov;V. Maltsev;M. Yurkin
通讯作者：
M. Yurkin
影响因子：
4.7
作者：
Siyao Shao;K. Mallery;Jiarong Hong
通讯作者：
Siyao Shao;K. Mallery;Jiarong Hong