Rogalski Mikolaj, Arcab Piotr, Wdowiak Emilia, Picazo-Bueno José Ángel, Micó Vicente, Józwik Michal, Trusiak Maciej
Warsaw University of Technology, Institute of Micromechanics and Photonics, 8 Sw. A. Boboli St., 02-525 Warsaw, Poland.
Departamento de Óptica y Optometría y Ciencias de la Visión, Universidad de Valencia, C/Doctor Moliner 50, 46100 Burjassot, Spain.
ACS Photonics. 2025 Jan 10;12(4):1771-1782. doi: 10.1021/acsphotonics.4c01863. eCollection 2025 Apr 16.
Achieving high-contrast, label-free imaging with minimal impact on live cell culture behavior remains a primary challenge in quantitative phase imaging (QPI). By enabling imaging under low illumination intensities (low photon budget, LPB), it is possible to minimize cell photostimulation, phototoxicity, and photodamage while supporting long-term and high-speed observations. However, LPB imaging introduces significant difficulties in QPI due to high levels of camera shot noise and quantification noise. Digital in-line holographic microscopy (DIHM) is a QPI technique known for its robustness against LPB data. However, simultaneous minimization of shot noise and inherent in DIHM twin image perturbation remains a critical challenge. In this study, we present the iterative Gabor averaging (IGA) algorithm, a novel approach that integrates iterative phase retrieval with frame averaging to effectively suppress both twin image disturbance and shot noise in multiframe DIHM. The IGA algorithm achieves this by leveraging an iterative process that reconstructs high-fidelity phase images while selectively averaging camera shot noise across frames. Our simulations demonstrate that IGA consistently outperforms conventional methods, achieving superior reconstruction accuracy, particularly under high-noise conditions. Experimental validations involving high-speed imaging of dynamic sperm cells and a static phase test target measurement under low illumination further confirmed IGA's efficacy. The algorithm also proved successful for optically thin samples, which often yield low signal-to-noise holograms even at high photon budgets. These advancements make IGA a powerful tool for photostimulation-free, high-speed imaging of dynamic biological samples and enhance the ability to image samples with extremely low optical thickness, potentially transforming biomedical and environmental applications in low-light settings.
在定量相位成像（QPI）中，实现高对比度、无标记成像且对活细胞培养行为影响最小，仍然是一项主要挑战。通过在低光照强度（低光子预算，LPB）下进行成像，可以在支持长期和高速观察的同时，将细胞光刺激、光毒性和光损伤降至最低。然而，由于相机散粒噪声和量化噪声水平较高，LPB成像给QPI带来了重大困难。数字同轴全息显微镜（DIHM）是一种以对LPB数据具有鲁棒性而闻名的QPI技术。然而，同时最小化散粒噪声和DIHM中固有的孪生图像扰动仍然是一个关键挑战。在本研究中，我们提出了迭代伽柏平均（IGA）算法，这是一种将迭代相位检索与帧平均相结合的新方法，可有效抑制多帧DIHM中的孪生图像干扰和散粒噪声。IGA算法通过利用一个迭代过程来实现这一点，该过程在重建高保真相位图像的同时，选择性地对各帧的相机散粒噪声进行平均。我们的模拟表明，IGA始终优于传统方法，在高噪声条件下尤其能实现更高的重建精度。涉及动态精子细胞高速成像和低光照下静态相位测试目标测量的实验验证进一步证实了IGA的有效性。该算法对光学薄样品也很成功，即使在高光子预算下，这些样品通常也会产生低信噪比的全息图。这些进展使IGA成为用于动态生物样品无光刺激、高速成像的强大工具，并增强了对极薄光学厚度样品成像的能力，有可能改变低光环境下的生物医学和环境应用。
