Regularized inverse holographic volume reconstruction for 3D particle tracking

Rapid flowing cells localization enabled by spatiotemporal manipulation of their holographic patterns

Lab-on-a-Chip microfluidic devices present an innovative and cost-effective platform in the current trend of miniaturization and simplification of imaging flow cytometry; they are excellent candidates for high-throughput single-cell analysis. In such microfluidic platforms, cell tracking becomes a fundamental tool for investigating biophysical processes, from intracellular dynamics to the characterization of cell motility and migration. However, high-throughput and long-term cell tracking puts a high demand on the consumption of computing resources. Here, we propose a novel strategy to achieve rapid 3D cell localizations along the microfluidic channel. This method is based on the spatiotemporal manipulation of recorded holographic interference fringes, and it allows fast and precise localization of cells without performing complete holographic reconstruction. Conventional holographic tracking is typically based on the phase contrast obtained by decoupling the calculation of optical axial and transverse coordinates. Computing time and resource consumption may increase because all the frames need to be calculated in the Fourier domain. In our proposed method, the 2D transverse positions are directly located by morphological calculation based on the hologram. The complex-amplitude wavefronts are directly reconstructed by spatiotemporal phase shifting to calculate the axial position by the refocusing criterion. Only spatial calculation is considered in the proposed method. We demonstrate that the computational time of transverse tracking is only one-tenth of the conventional method, while the total computational time of the proposed method decreases up to 54% with respect to the conventional approach. The proposed approach can open the route for analyzing flow cytometry in quantitative phase microscopy assays.

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.

Ultraviolet digital holographic microscopy (DHM) of micron-scale particles from shocked Sn ejecta

A cloud of very fast, O(km/s), and very fine, O(µm), particles may be ejected when a strong shock impacts and possibly melts the free surface of a solid metal. To quantify these dynamics, this work develops an ultraviolet, long-working distance, two-pulse Digital Holographic Microscopy (DHM) configuration and is the first to replace film recording with digital sensors for this challenging application. A proposed multi-iteration DHM processing algorithm is demonstrated for automated measures of the sizes, velocities, and three-dimensional positions of non-spherical particles. Ejecta as small as 2 µm diameter are successfully tracked, while uncertainty simulations indicate that particle size distributions are accurately quantified for diameters ≥4 µm. These techniques are demonstrated on three explosively driven experiments. Measured ejecta size and velocity statistics are shown to be consistent with prior film-based recording, while also revealing spatial variations in velocities and 3D positions that have yet to be widely investigated. Having eliminated time-consuming analog film processing, the methodologies proposed here are expected to significantly accelerate future experimental investigation of ejecta physics.

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.

Accurate automatic object 4D tracking in digital in-line holographic microscopy based on computationally rendered dark fields

Building on Gabor seminal principle, digital in-line holographic microscopy provides efficient means for space-time investigations of large volumes of interest. Thus, it has a pivotal impact on particle tracking that is crucial in advancing various branches of science and technology, e.g., microfluidics and biophysical processes examination (cell motility, migration, interplay etc.). Well-established algorithms often rely on heavily regularized inverse problem modelling and encounter limitations in terms of tracking accuracy, hologram signal-to-noise ratio, accessible object volume, particle concentration and computational burden. This work demonstrates the DarkTrack algorithm-a new approach to versatile, fast, precise, and robust 4D holographic tracking based on deterministic computationally rendered high-contrast dark fields. Its unique capabilities are quantitatively corroborated employing a novel numerical engine for simulating Gabor holographic recording of time-variant volumes filled with predefined dynamic particles. Our solution accounts for multiple scattering and thus it is poised to secure an important gap in holographic particle tracking technology and allow for ground-truth-driven benchmarking and quantitative assessment of tracking algorithms. Proof-of-concept experimental evaluation of DarkTrack is presented via analyzing live spermatozoa. Software supporting both novel numerical holographic engine and DarkTrack algorithm is made open access, which opens new possibilities and sets the stage for democratization of robust holographic 4D particle examination.

Holographic 3D particle reconstruction using a one-stage network

Volumetric reconstruction of a three-dimensional (3D) particle field with high resolution and low latency is an ambitious and valuable task. As a compact and high-throughput imaging system, digital holography (DH) encodes the 3D information of a particle volume into a two-dimensional (2D) interference pattern. In this work, we propose a one-stage network (OSNet) for 3D particle volumetric reconstruction. Specifically, by a single feed-forward process, OSNet can retrieve the 3D coordinates of the particles directly from the holograms without high-fidelity image reconstruction at each depth slice. Evaluation results from both synthetic and experimental data confirm the feasibility and robustness of our method under different particle concentrations and noise levels in terms of detection rate and position accuracy, with improved processing speed. The additional applications of 3D particle tracking are also investigated, facilitating the analysis of the dynamic displacements and motions for micro-objects or cells. It can be further extended to various types of computational imaging problems sharing similar traits.

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.

Influence of sparse constraint functions on compressive holographic tomography

In this paper, we quantified and analyzed the impact of the l₁ norm and total variation (TV) norm sparse constraints on the reconstruction quality under different interlayer spacings, sampling rates, and signal-to-noise ratios. For high-quality holograms, the results of compressive-sensing reconstruction using l₁ norm achieved higher quality than those by the TV norm. In contrast, for low-quality holograms, the quality of TV-norm-based reconstruction results was relatively stable and better than that of l₁ norm. In addition, we explained why interlayer spacing cannot be smaller and recommend the use of axial resolution of the digital holography system as the interlayer spacing. The conclusions are valuable in the choice of sparse constraints in compressive holographic tomography.

Separating twin images in digital holographic microscopy using weak scatterers

When using inline digital holographic microscopy (DHM) and placing the hologram plane within a particle suspension, both real and virtual images come into focus during reconstruction, limiting our ability to resolve three-dimensional (3D) particle distribution. Here, we propose a new method to distinguish between real and virtual images in the 3D reconstruction field. This new method is based on the use of weak scatterers, and the fact that the real and virtual images of weak scatterers display distinct intensity distributions along the optical axis. We experimentally demonstrate this method by localizing and tracking 1 µm particles in a 3D volume with a particle concentration ranging from 200 to 6000particles/mm³. Unlike previous approaches to address the virtual image problem, this method does not require the recording of multiple holograms or the insertion of additional optical components. The proposed method allows the hologram plane to be placed within the sample volume, and extends the capability of DHM to measure the 3D movements of particles in deep samples far away from the optical window.

Axial resolution analysis in compressive digital holographic microscopy

Digital holographic microscopy with compressive sensing (CDHM) has successfully achieved tomography and has been applied in many fields. However, the enhancement of axial resolution in CDHM remains to be elucidated. By deducing accurate formulas for the lateral and axial resolutions without paraxial approximation, we quantized the elongation effect of a digital holography (DH) system in this study. Thus, we revealed that the elongation effect, which is affected only by the system's numerical aperture (NA), is an inherent property of DH systems. We present a detailed analysis herein on the physical significance of the coherence parameter, which is the ratio of a system's limit axial resolution to the interlayer spacing more thoroughly than in previous research. Further, we achieved the tomography of a fiber by using a DH system with a 10 × microscope, with CS to eliminate the elongation effect, and experimentally validated our theoretical results. By applying these theoretical guidelines, we distinguished crossed fibers at distances of 36.4 μm and 48.5 μm, respectively, using the same experimental setup. There would be potential applications of this theory in tomography and observation of microscale objects in the areas of biological and fluid.

Machine learning holography for 3D particle field imaging

We propose a new learning-based approach for 3D particle field imaging using holography. Our approach uses a U-net architecture incorporating residual connections, Swish activation, hologram preprocessing, and transfer learning to cope with challenges arising in particle holograms where accurate measurement of individual particles is crucial. Assessments on both synthetic and experimental holograms demonstrate a significant improvement in particle extraction rate, localization accuracy and speed compared to prior methods over a wide range of particle concentrations, including highly dense concentrations where other methods are unsuitable. Our approach can be potentially extended to other types of computational imaging tasks with similar features.

Microalgal swimming signatures and neutral lipids production across growth phases

Microalgae have been shown as a potential bioresource for food, biofuel, and pharmaceutical products. During the growth phases with corresponding environmental conditions, microalgae accumulate different amounts of various metabolites. We quantified the neutral lipids accumulation and analyzed the swimming signatures (speed and trajectories) of the motile green alga, Dunaliella primolecta, during the lag-exponential-stationary growth cycle at different nutrient concentrations. We discovered significant changes in the neutral lipid content and swimming signatures of microalgae across growth phases. The timing of the maximum swimming speed coincided with the maximum neutral lipid content and both maxima occurred under nutrient stress at the stationary growth phase. Furthermore, the swimming trajectories suggested statistically significant changes in swimming modes at the stationary growth phase when the maximum intracellular neutral lipid content was observed. Our results provide the potential exploitation of microalgal swimming signatures as possible indicators of the cultivation conditions and the timing of microalgal harvest to maximize the lipid yield for biofuel production. The findings can also be implemented to explore the production of food and antibiotics from other microalgal metabolites with low energy costs.