Separating twin images in digital holographic microscopy using weak scatterers

Digital in-line holographic microscopy for label-free identification and tracking of biological cells

Digital in-line holographic microscopy (DIHM) is a non-invasive, real-time, label-free technique that captures three-dimensional (3D) positional, orientational, and morphological information from digital holographic images of living biological cells. Unlike conventional microscopies, the DIHM technique enables precise measurements of dynamic behaviors exhibited by living cells within a 3D volume. This review outlines the fundamental principles and comprehensive digital image processing procedures employed in DIHM-based cell tracking methods. In addition, recent applications of DIHM technique for label-free identification and digital tracking of various motile biological cells, including human blood cells, spermatozoa, diseased cells, and unicellular microorganisms, are thoroughly examined. Leveraging artificial intelligence has significantly enhanced both the speed and accuracy of digital image processing for cell tracking and identification. The quantitative data on cell morphology and dynamics captured by DIHM can effectively elucidate the underlying mechanisms governing various microbial behaviors and contribute to the accumulation of diagnostic databases and the development of clinical treatments.

Improving the Signal-to-Noise Ratio of Axial Displacement Measurements of Microspheres Based on Compound Digital Holography Microscopy Combined with the Reconstruction Centering Method

In 3D microsphere tracking, unlike in-plane motion that can be measured directly by a microscope, axial displacements are resolved by optical interference or a diffraction model. As a result, the axial results are affected by the environmental noise. The immunity to environmental noise increases with measurement accuracy and the signal-to-noise ratio (SNR). In compound digital holography microscopy (CDHM)-based measurements, precise identification of the tracking marker is critical to ensuring measurement precision. The reconstruction centering method (RCM) was proposed to suppress the drawbacks caused by installation errors and, at the same time, improve the correct identification of the tracking marker. The reconstructed center is considered to be the center of the microsphere, rather than the center of imaging in conventional digital holographic microscopy. This method was verified by simulation of rays tracing through microspheres and axial moving experiments. The axial displacements of silica microspheres with diameters of 5 μm and 10 μm were tested by CDHM in combination with the RCM. As a result, the SNR of the proposed method was improved by around 30%. In addition, the method was successfully applied to axial displacement measurements of overlapped microspheres with a resolution of 2 nm.

Comparison of three-dimensional motion of bacteria with and without wall accumulation

A comparison of the movement characteristics between bacteria with and without wall accumulation could potentially elucidate the mechanisms of biofilm formation. However, authors of previous studies have mostly focused on the motion of bacteria that exhibit wall accumulation. Here, we applied digital holographic microscopy to compare the three-dimensional (3D) motions of two bacterial strains (Shewanella japonica UMDC19 and Shewanella sp. UMDC1): one exhibiting higher concentrations near the solid surfaces, and the other showing similar concentrations in near-wall and bulk regions. We found that the movement characteristics of the two strains are similar in the near-wall region but are distinct in the bulk region. Near the wall, both strains have small velocities and mostly perform subdiffusive motions. In the bulk, however, the bacteria exhibiting wall accumulation have significantly higher motility (including faster swimming speeds and longer movement trajectories) than the one showing no wall accumulation. Furthermore, we found that bacteria exhibiting wall accumulation slowly migrate from the bulk region to the near-wall region, and the hydrodynamic effect alone is insufficient to generate this migration speed. Future studies are required to test if the current findings apply to other bacterial species and strains.

Deep learning assisted holography microscopy for in-flow enumeration of tumor cells in blood

Currently, detection of circulating tumor cells (CTCs) in cancer patient blood samples relies on immunostaining, which does not provide access to live CTCs, limiting the breadth of CTC-based applications. Here, we take the first steps to address this limitation, by demonstrating staining-free enumeration of tumor cells spiked into lysed blood samples using digital holographic microscopy (DHM), microfluidics and machine learning (ML). A 3D-printed module for laser assembly was developed to simplify the optical set up for holographic imaging of cells flowing through a sheath-based microfluidic device. Computational reconstruction of the holograms was performed to localize the cells in 3D and obtain the plane of best focus images to train deep learning models. We developed a custom-designed light-weight shallow Network dubbed s-Net and compared its performance against off-the-shelf CNN models including ResNet-50. The accuracy, sensitivity and specificity of the s-Net model was found to be higher than the off-the-shelf ML models. By applying an optimized decision threshold to mixed samples prepared in silico, the false positive rate was reduced from 1 × 10^-2 to 2.77 × 10^-4. Finally, the developed DHM-ML framework was successfully applied to enumerate spiked MCF-7 breast cancer cells and SkOV3 ovarian cancer cells from lysed blood samples containing white blood cells (WBCs) at concentrations typical of label-free enrichment techniques. We conclude by discussing the advances that need to be made to translate the DHM-ML approach to staining-free enumeration of actual CTCs in cancer patient blood samples.

Effect of hologram plane position on particle tracking using digital holographic microscopy

This paper discusses the effect of hologram plane position on the tracking of particle motions in a 3D suspension using digital holography microscopy. We compare two optical configurations where the hologram plane is located either just outside the particle suspension or in the middle of the suspension. In both cases, we record two axially separated holograms using two cameras and subsequently adopt an iterative phase retrieval approach to solve the virtual image problem. We measure the settling motions of 2 µm spheres in a 2 mm thick sample containing 300 to 1500p a r t i c l e s/m m ³. We show that the optical setup where the hologram plane is located in the middle of the sample provides superior tracking results compared to the other, including higher accuracy in the measurement of particle displacement and longer particle trajectories. The accuracy of particle displacement increases by a maximum of 18%, and the trajectory length increases by a maximum of 16%. This superior outcome is due to the less overlapping of the diffraction patterns on the holograms when the separation distance between particles and the hologram plane is minimized.

Improving axial localization of weak phase particles in digital in-line holography

One shortcoming of digital in-line holography (DIH) is the low axial position accuracy due to the elongated particle traces in the reconstruction field. Here, we propose a method that improves the axial localization of DIH when applying it to track the motion of weak phase particles in dense suspensions. The proposed method detects particle positions based on local intensities in the reconstruction field consisting of scattering and incident waves. We perform both numerical and experimental tests and demonstrate that the proposed method has a higher axial position accuracy than the previous method based on the local intensities in the reconstructed scattered field. We show that the proposed method has an axial position error below 1.5 particle diameters for holograms with a particle concentration of 4700particles/mm³. The proposed method is further validated by tracking the Brownian motion of 1µmparticles in dense suspensions.