Intensity shot noise in digital holograms distorts the quality of the phase images after phase retrieval, limiting the usefulness of quantitative phase microscopy (QPM) systems in long term live cell imaging. In this paper, we devise a hologram-to-hologram neural network, Holo-UNet, that restores high quality digital holograms under high shot noise conditions (sub-mW/cm² intensities) at high acquisition rates (sub-milliseconds). In comparison to current phase recovery methods, Holo-UNet denoises the recorded hologram, and so prevents shot noise from propagating through the phase retrieval step that in turn adversely affects phase and intensity images. Holo-UNet was tested on 2 independent QPM systems without any adjustment to the hardware setting. In both cases, Holo-UNet outperformed existing phase recovery and block-matching techniques by ∼ 1.8 folds in phase fidelity as measured by SSIM. Holo-UNet is immediately applicable to a wide range of other high-speed interferometric phase imaging techniques. The network paves the way towards the expansion of high-speed low light QPM biological imaging with minimal dependence on hardware constraints.

中文翻译：

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Holo-UNet：全息图至全息图神经网络还原，用于活细胞的高保真低光定量相位成像

数字全息图中的强度散粒噪声会扭曲相位检索后的相位图像质量，从而限制了定量相位显微镜（QPM）系统在长期活细胞成像中的实用性。在本文中，我们设计了全息图至全息图的神经网络Holo-UNet，该网络可在高散粒噪声条件下（sub-mW / cm ^2）恢复高质量的数字全息图。强度（高毫秒级）。与当前的相位恢复方法相比，Holo-UNet对记录的全息图进行降噪，从而防止散粒噪声在相位恢复步骤中传播，进而对相位和强度图像产生不利影响。Holo-UNet在2个独立的QPM系统上进行了测试，而无需对硬件设置进行任何调整。在这两种情况下，Holo-UNet的相保真度均优于现有的相恢复和块匹配技术，如SSIM所测，相保真度约为1.8倍。Holo-UNet可立即应用于多种其他高速干涉式相位成像技术。该网络为扩展高速微光QPM生物成像铺平了道路，而对硬件限制的依赖性却很小。