混合迭代-平均低光子预算Gabor全息显微术
Hybrid iterating-averaging low photon budget Gabor holographic microscopy
AI总结：
针对低光子预算下数字同轴全息显微术的噪声与孪生图像干扰问题，提出迭代Gabor平均（IGA）算法，提升了高噪声下的重建精度，实现了动态生物样本的高速无光刺激成像。
摘要：
活细胞培养观察中的主要挑战之一是在对样本行为影响最小的情况下实现高对比度成像。定量相位成像（QPI）技术通过提供透明样本的无标记、高对比度图像来解决这一问题。在低照明强度（低光子预算 - LPB）下对样本进行成像，可进一步降低测量系统的影响，从而最大程度地减少光刺激、光毒性和光损伤，并实现高速成像。由于显著的相机散粒噪声和量化噪声，LPB成像在QPI中极具挑战性。数字同轴全息显微术（DIHM）有无透镜均可工作，是一种以对量化噪声具有鲁棒性而闻名的QPI技术。然而，同时降低相机散粒噪声和固有的同轴全息孪生图像干扰仍然是一个关键但尚未解决的挑战。本研究引入了一种创新的迭代Gabor平均（IGA）算法，专门用于填补LPB条件下多帧DIHM中这一重要的科学空白。我们在模拟数据上评估了IGA的性能，结果表明在高噪声条件下，其在重建精度方面优于传统算法。这些结果通过实验验证得到了证实，该实验涉及在显著降低的照明功率下对动态精子细胞和相位测试靶标的高速成像。此外，IGA算法被证明在重建光学薄样本方面也很成功，这类样本即使在高光子预算条件下通常也会产生低信噪比的全息图。这些进展促进了对动态生物样本的无光刺激和高速成像，并增强了对极低光学厚度样本的成像能力，有望彻底改变生物医学和环境成像中的各种应用。
英文摘要：
One of the primary challenges in live cell culture observation is achieving high-contrast imaging with minimal impact on sample behavior. Quantitative phase imaging (QPI) techniques address this by providing label-free, high-contrast images of transparent samples. Measurement system influence may be further reduced by imaging samples under low illumination intensity (low photon budget - LPB), thereby minimizing photostimulation, phototoxicity, and photodamage, and enabling high-speed imaging. LPB imaging is challenging in QPI due to significant camera shot noise and quantification noise. Digital in-line holographic microscopy (DIHM), working with or without lenses, is a QPI technique known for its robustness to quantification noise. However, reducing simultaneously the camera shot noise and the inherent in-line holographic twin image disturbances remain a critical, yet unaddressed, challenge. This study introduces an innovative iterative Gabor averaging (IGA) algorithm designed specifically for filling this important scientific gap in multi-frame DIHM under LPB conditions. We evaluated the performance of the IGA on simulated data showing that it outperformed traditional algorithms in terms of reconstruction accuracy under high noise conditions. Those results were corroborated by experimental validation involving high-speed imaging of dynamic sperm cells and a phase test target under significantly reduced illumination power. Additionally, the IGA algorithm proved successful in reconstructing optically thin samples, which typically produce low signal-to-noise ratio holograms even under high photon budget conditions. These advancements facilitate photostimulation-free and high-speed imaging of dynamic biological samples and enhance the capability to image samples with extremely low optical thickness, potentially transforming various applications in biomedical and environmental imaging.
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