Live cell imaging is challenging because the difficult balance of maintaining both cell viability and high signal to noise ratio throughout the entire imaging duration. Label free quantitative light microscopy techniques are powerful tools to image the volumetric activities in living cellular and sub-cellular biological systems, however there are minimal ways to identify phototoxicity. In this paper, we investigate the use of neural network to restore quantitative digital hologram micrographs at ultra-low light levels down to 0.06 𝑚𝑊/𝑐𝑚2 which approximately two orders of magnitude lower than sunlight. By developing an adaptive image restoration method specifically tailored for digital holograms, we demonstrated the 2x improvement in SSIM over existing denoising methods. This demonstration could open up new avenues for high resolution holographic microscopy using deep ultraviolet coherent sources and achieve high-resolution imaging with ultralow light illumination.
Digital Holographic Microscopy (DHM) has emerged as a powerful imaging tool due to its ability to provide quantitative sample morphological data in a label-free manner. Off-axis holography further opens possibilities of numerical approaches to image analysis and data processing. However, this involves computationally heavy workflows that limit the tool’s usability in biomedical research. In this paper, a software package is developed for off-axis hologram reconstruction and processing. The software can perform a variety of bioimaging operations including imaging, region of interest selection, automated reconstruction, and data extraction, with a user-friendly graphical user interface. Originally programmed in MATLAB, the software can be installed to use in common lab-based Microsoft Windows computers. The software can be easily adopted to work with customized off-axis DHM setups, aiming to increase the efficiency of DHM’s bioimaging workflow in the community. To demonstrate this software, blood platelet experiments were conducted to show quantitative volume change of thrombus formation.