Characterization and identification of cell death dynamics by quantitative phase imaging

Deep-learning based 3D birefringence image generation using 2D multi-view holographic images

Refractive index stands as an inherent characteristic of a material, allowing non-invasive exploration of the three-dimensional (3D) interior of the material. Certain materials with different refractive indices produce a birefringence phenomenon in which incident light is split into two polarization components when it passes through the materials. Representative birefringent materials appear in calcite crystals, liquid crystals (LCs), biological tissues, silk fibers, polymer films, etc. If the internal 3D shape of these materials can be visually expressed through a non-invasive method, it can greatly contribute to the semiconductor, display industry, optical components and devices, and biomedical diagnosis. This paper introduces a novel approach employing deep learning to generate 3D birefringence images using multi-viewed holographic interference images. First, we acquired a set of multi-viewed holographic interference pattern images and a 3D volume image of birefringence directly from a polarizing DTT (dielectric tensor tomography)-based microscope system about each LC droplet sample. The proposed model was trained to generate the 3D volume images of birefringence using the two-dimensional (2D) interference pattern image set. Performance evaluations were conducted against the ground truth images obtained directly from the DTT microscopy. Visualization techniques were applied to describe the refractive index distribution in the generated 3D images of birefringence. The results show the proposed method's efficiency in generating the 3D refractive index distribution from multi-viewed holographic interference images, presenting a novel data-driven alternative to traditional methods from the DTT devices.

Detectability of unresolved particles in off-axis digital holographic microscopy

Off-axis digital holographic microscopy (DHM) provides both amplitude and phase images, and so it may be used for label-free 3D tracking of micro- and nano-sized particles of different compositions, including biological cells, strongly absorbing particles, and strongly scattering particles. Contrast is provided by differences in either the real or imaginary parts of the refractive index (phase contrast and absorption) and/or by scattering. While numerous studies have focused on phase contrast and improving resolution in DHM, particularly axial resolution, absent have been studies quantifying the limits of detection for unresolved particles. This limit has important implications for microbial detection, including in life-detection missions for space flight. Here we examine the limits of detection of nanosized particles as a function of particle optical properties, microscope optics (including camera well depth and substrate), and data processing techniques and find that DHM provides contrast in both amplitude and phase for unresolved spheres, in rough agreement with Mie theory scattering cross-sections. Amplitude reconstructions are more useful than phase for low-index spheres and should not be neglected in DHM analysis.

Comparative analysis of Radachlorin accumulation, localization, and photobleaching in three cell lines by means of holographic and fluorescence microscopy

In this paper we compare the response of cells of established lines of different origin: HeLa, A549 and 3T3 to photodynamic treatment with Radachlorin photosensitizer. The analysis was performed on different aspects of the treatment procedure including photosensitizer accumulation, localization and photobleaching in cells and post-treatment dynamics of changes in cellular morphology at different treatment doses. It was shown that in the three cell lines Radachlorin accumulated in lysosomes to much greater extent than in mitochondria. The cells' response to treatment was analyzed by identification of their death pathways and evaluation of average phase shift dynamics using digital holographic microscopy. The analysis performed on the three cell lines allowed us to evaluate treatment doses specific for each pathway in each line. Among the three lines HeLa cells were found to be the most susceptible to treatment while 3T3 cells the most resistant. The comparison of these results with the data on Radachlorin accumulation, localization and photobleaching rates showed that the observed higher sensitivity of HeLa cells to photodynamic treatment correlated with higher photosensitizer uptake and more intensive photobleaching while lower sensitivity of 3T3 cells correlated with lower uptake and less intensive photobleaching.