Digital Holographic Microscopy Research Articles

Motion history images: a new method for tracking microswimmers in 3D

Quantitative tracking of rapidly moving micron-scale objects remains an elusive challenge in microscopy due to low signal-to-noise. This paper describes a novel method for tracking micron-sized motile organisms in off-axis Digital Holographic Microscope (DHM) raw holograms and/or reconstructions. We begin by processing the microscopic images with the previously reported Holographic Examination for Life-like Motility (HELM) software, which provides a variety of tracking outputs including motion history images (MHIs). MHIs are stills of videos where the frame-to-frame changes are indicated with color time-coding. This exposes tracks of objects that are difficult to identify in individual frames at a low signal-to-noise ratio. The visible tracks in the MHIs are superior to tracks identified by all tested automated tracking algorithms that start from object identification at the frame level, particularly in low signal-to-noise ratio data, but do not provide quantitative track data. In contrast to other tracking methods, like Kalman filter, where the recording is analyzed frame by frame, MHIs show the whole time span of particle movement at once and eliminate the need to identify objects in individual frames. This feature also enables post-tracking identification of low-SNR objects. We use these tracks, rather than object identification in individual frames, as a basis for quantitative tracking of Bacillus subtilis by first generating MHIs from X, Y, and t stacks (raw holograms or a projection over reconstructed planes), then using a region-tracking algorithm to identify and separate swimming pathways. Subsequently, we identify each object's Z plane of best focus at the corresponding X, Y, and t points, yielding ap full description of the swimming pathways in three spatial dimensions plus time. This approach offers an alternative to object-based tracking for processing large, low signal-to-noise datasets containing highly motile organisms.

Quantitative phase image stitching guided by reconstructed intensity images in one-shot double field of view multiplexed digital holographic microscopy

Quantitative phase image stitching guided by reconstructed intensity images in one-shot double field of view multiplexed digital holographic microscopy

Illumination system contributing zooming function to lensless digital holographic microscope by using lightguide incorporated with volume holographic optical elements

Illumination systems play a crucial role in determining the image quality of lens- less images. In this paper, we propose an illumination system that uses a light guide with a volume holographic optical element (VHOE) and apply it to a lensless digital holographic microscope (DHM). The light guide has an in-coupler that is maturely developed for AR/MR applications. A VHOE serves as an in-coupler and directs the laser light into the guiding mode. Unlike the conventional light guide in the AR/MR application, the out-coupler is changed to a functional VHOE to diffract a divergent spherical wave. Through clever arrangement, the interference fringe caught by the CMOS image sensor can be used to retrieve the tested image. By controlling the focusing point of the diffracted spherical wave, the field of view (FOV) and the resolution can be adjusted. We have demonstrated the use of different VHOEs to perform different FOV and image resolutions. Thus, a zoomable-compact lensless DHM with holographic light guide technology is achievable.

Application of Digital Holographic Imaging to Monitor Real-Time Cardiomyocyte Hypertrophy Dynamics in Response to Norepinephrine Stimulation

Cardiomyocyte hypertrophy, characterized by an increase in cell size, is associated with various cardiovascular diseases driven by factors including hypertension, myocardial infarction, and valve dysfunction. In vitro primary cardiomyocyte culture models have yielded numerous insights into the intrinsic and extrinsic mechanisms driving hypertrophic growth. However, due to limitations in current approaches, the dynamics of cardiomyocyte hypertrophic responses remain poorly characterized. In this study, we evaluate the application of the Holomonitor M4 digital holographic imaging microscope to track dynamic changes in cardiomyocyte surface area and volume in response to norepinephrine treatment, a model hypertrophic stimulus. The Holomonitor M4 permits non-invasive, label-free imaging of three-dimensional changes in cell morphology with minimal phototoxicity, thus enabling long-term imaging studies. Untreated and norepinephrine-stimulated primary neonatal rat cardiomyocytes were live-imaged on the Holomonitor M4, which was followed by image segmentation and single-cell tracking using the HOLOMONITOR App Suite software version 4.0.1.546. The 24 h treatment of cultured cardiomyocytes with norepinephrine increased cardiomyocyte spreading and optical volume as expected, validating the reliability of the approach. Single-cell tracking of both cardiomyocyte surface area and three-dimensional optical volume revealed dynamic increases in these parameters throughout the 24 h imaging period, demonstrating the potential of this technology to explore cardiomyocyte hypertrophic responses with greater temporal resolution; however, technological limitations were also observed and should be considered in the experimental design and interpretation of results. Overall, leveraging the unique advantages of the Holomonitor M4 digital holographic imaging system has the potential to empower future work towards understanding the molecular and cellular mechanisms underlying cardiomyocyte hypertrophy with enhanced temporal clarity.

Real-time 3D tracking of swimming microbes using digital holographic microscopy and deep learning.

The three-dimensional swimming tracks of motile microorganisms can be used to identify their species, which holds promise for the rapid identification of bacterial pathogens. The tracks also provide detailed information on the cells' responses to external stimuli such as chemical gradients and physical objects. Digital holographic microscopy (DHM) is a well-established, but computationally intensive method for obtaining three-dimensional cell tracks from video microscopy data. We demonstrate that a common neural network (NN) accelerates the analysis of holographic data by an order of magnitude, enabling its use on single-board computers and in real time. We establish a heuristic relationship between the distance of a cell from the focal plane and the size of the bounding box assigned to it by the NN, allowing us to rapidly localise cells in three dimensions as they swim. This technique opens the possibility of providing real-time feedback in experiments, for example by monitoring and adapting the supply of nutrients to a microbial bioreactor in response to changes in the swimming phenotype of microbes, or for rapid identification of bacterial pathogens in drinking water or clinical samples.

Precise Refractive Index Measurement of Fused Silica Optics

Abstract We've developed an experimental platform that non-destructively and precisely measures the Refractive Index (RI) and dispersion of ultra-polished fused silica optics. Using Total Internal Reflection Digital Holographic Microscopy (TIRDHM), we exploit the phase change of reflected light in Total Internal Reflection (TIR) mode. This phase change depends on the incident angle at the TIR interface and the refractive indices of the involved media. We've optimized a combination of higher TIR phase sensitivity, considerable penetration depth, and minimized phase measurement inaccuracies through simulations to design our experiment. Key features include a custom-made precision Right-Angle Prism (RAP) of Astrositall material, a seamless interface with fused silica optics on TIR interface through optical contact, and single-shot measurement. We've demonstrated the accuracy of measuring fused silica optics through proof of concept and experimental results. Our measurements on two different samples show accuracy better than ± 3 x 10-4 compared to those obtained using a commercially available critical angle Refractometer (Metricon). Importantly, the setup offers the advantage of spatially mapping the refractive index, unlike point measurements by available Refractometers.

Improvement of Fresnel Diffraction Convolution Algorithm

With the development of digital holography, the accuracy requirements for the reconstruction phase are becoming increasingly high. The transfer function of the double fast transform (D-FFT) algorithm is distorted when the diffraction distance is larger than the criterion distance dt, which reduces the accuracy of solving the phase. In this paper, the Fresnel diffraction integration algorithm is improved by using the low-pass Tukey window to obtain more accurate reconstructed phases. The improved algorithm is called the D-FFT (Tukey) algorithm. The D-FFT (Tukey) algorithm adjusts the degree of edge smoothing of the Tukey window, using the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) to remove the ringing effect and obtain a more accurate reconstructed phase. In a simulation of USAF1951, the longitudinal resolution of the reconstructed phase obtained by D-FFT (Tukey) reached 1.5 μm, which was lower than the 3 μm obtained by the T-FFT algorithm. The results of Fresnel holography experiments on lung cancer cell slices also demonstrated that the phase quality obtained by the D-FFT (Tukey) algorithm was superior to that of the T-FFT algorithm. D-FFT (Tukey) algorithm has potential applications in phase correction, structured illumination digital holographic microscopy, and microscopic digital holography.

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.

Grading of glioma tumors using digital holographic microscopy

Gliomas are the most common type of cerebral tumors; they occur with increasing incidence in the last decade and have a high rate of mortality. For efficient treatment, fast accurate diagnostic and grading of tumors are imperative. Presently, the grading of tumors is established by histopathological evaluation, which is a time-consuming procedure and relies on the pathologists’ experience. Here we propose a supervised machine learning procedure for tumor grading which uses quantitative phase images of unstained tissue samples acquired by digital holographic microscopy. The algorithm is using an extensive set of statistical and texture parameters computed from these images. The procedure has been able to classify six classes of images (normal tissue and five glioma subtypes) and to distinguish between gliomas types from grades II to IV (with the highest sensitivity and specificity for grade II astrocytoma and grade III oligodendroglioma and very good scores in recognizing grade III anaplastic astrocytoma and grade IV glioblastoma). The procedure bolsters clinical diagnostic accuracy, offering a swift and reliable means of tumor characterization and grading, ultimately the enhancing treatment decision-making process.

Detecting material state changes in the nucleolus by label-free digital holographic microscopy.

Ribosome biogenesis is initiated in the nucleolus, a multiphase biomolecular condensate formed by liquid-liquid phase separation. The nucleolus is a powerful disease biomarker and stress biosensor whose morphology reflects function. Here we have used digital holographic microscopy (DHM), a label-free quantitative phase contrast microscopy technique, to detect nucleoli in adherent and suspension human cells. We trained convolutional neural networks to detect and quantify nucleoli automatically on DHM images. Holograms containing cell optical thickness information allowed us to define a novel index which we used to distinguish nucleoli whose material state had been modulated optogenetically by blue-light-induced protein aggregation. Nucleoli whose function had been impacted by drug treatment or depletion of ribosomal proteins could also be distinguished. We explored the potential of the technology to detect other natural and pathological condensates, such as those formed upon overexpression of a mutant form of huntingtin, ataxin-3, or TDP-43, and also other cell assemblies (lipid droplets). We conclude that DHM is a powerful tool for quantitatively characterizing nucleoli and other cell assemblies, including their material state, without any staining.

Improvement of digital Gabor holographic microscopy using a lens in plankton studies

This work utilizes a Gabor Holographic Optical Scheme integrated with a microscope objective and a thin convex plane lens. This bi-telecentric lens system corrects spherical aberration from the objective, maintains consistent magnification across various reconstruction distances, and ensures a plane incidence on CMOS. Depending on the focal lengths of the objective and lens, the final image can be enlarged or reduced compared to the classic Gabor system, resulting in high-quality reconstructed phase images without spherical aberration. This setup was employed to capture phase distribution and intensity images of planktonic objects, such as copepods, achieving superior image quality.

Dynamic Inhibition of Calcite Dissolution in Flowing Acidic Pb2+ Solutions.

Reactions of mineral surfaces with dissolved metal ions at far-from-equilibrium conditions can deviate significantly from those in near-equilibrium systems due to steep concentration gradients, ion-surface interactions, and reactant transport effects that can lead to emergent behavior. We explored the effect of dissolved Pb2+ on the dissolution rate and topographic evolution of calcite (104) surfaces under far-from-equilibrium acidic conditions (pH 3.7) in a confined single-pass laminar-flow geometry. Operando measurements by digital holographic microscopy were conducted over a range of Pb2+ concentrations ([Pb2+] = 0 to 5 × 10-2 M) and flow velocities (v = 1.67-53.3 mm s-1). Calcite (104) surface dissolution rates decreased with increasing [Pb2+]. The inhibition of dissolution and the emergence of unique topographic features, including micropyramids, variable etch pit shapes, and larger scale topographic patterns, became increasingly apparent at [Pb2+] ≥ 5 × 10-3 M. A better understanding of such dynamic reactivity could be crucial for constructing accurate models of geochemical transport in aqueous carbonate systems.

Drop-on-Demand Pyro-Electrohydrodynamic Printing of Nematic Liquid Crystal Microlenses.

Inkjet printing of liquid crystal (LC) microlens arrays is particularly appealing for the development of switchable 2D/3D organic light-emitting diode (OLED) displays, as the printing process ensures that the lenses can be deposited directly and on-demand onto the pixelated OLED layer without the need for additional steps, thus simplifying fabrication complexity. Even if different fabrication technologies have been employed and good results in LC direct printing have already been achieved, all the systems used require costly equipment and heated nozzles to reduce the LC solution's viscosity. Here, we present the direct printing of a nematic LC (NLC) lens by a Drop-on-Demand (DoD) inkjet printing by a pyro-electrohydrodynamic effect for the first time. The method works at ambient temperature and avoids dispensing nozzles, thus offering a noncontact manipulation approach of liquid with high resolution and good repeatability on different kinds of substrates. NLC microlenses are printed on different substrates and fully characterized. Polarization properties are evaluated for various samples, i.e., NLC lenses on unaligned and indium-tin oxide (ITO) aligned. Moreover, an in-depth characterization of the NLC lenses is reported by polarized optical microscopy and by analyzing the birefringence in digital holographic microscopy.

Improving cellular analysis throughput of lens-free holographic microscopy with circular Hough transform and convolutional neural networks

In recent years, lens-free Digital In-Line Holographic Microscopy (DIHM) has become an essential tool for in-vitro experiments. Specifically, it offers many innovative approaches to the characterization of cancer cell assays, which are pioneering studies in the prevention and treatment of cancer, the most common disease of our time. With DIHM, images with very high resolution, high magnification coefficient, and wide FOV can be obtained. However, the success of the DIHM is directly dependent on the successful coordination of the imaging and analysis processes. This study proposes a combined approach of circular Hough transform (CHT) and Convolutional Neural Network (CNN) algorithms to improve the cellular analysis aspect of DIHM. The design, installation, and testing of the DIHM for cellular imaging are presented. Resolution analyses of the microscopy system are presented using a standard USAF 1951 resolution slide. MCF-7 cell lines were imaged with the designed microscope at various concentrations. CHT was used in the wide search space to detect the particles in the cell slides. The proposed method detected all overlapping cells and non-cell particles in the images. CNN was used to classify particles as living, dead, and noncell cells. A GPU-based GUI has been designed to perform imaging and analysis operations. The performance of the proposed method is statistically compared with a reference system using various performance metrics. The accuracy of the model is calculated as %99.92 and also the results obtained with the proposed method show more than R2=0.99 correlation with a reference system. The results of the proposed method have improved the analytical performance of DIHM in in-vitro cell cancer cell line experiments. In addition, the method contributes to the analysis of high-resolution images.

Abstract 2530: Advancing ICK assay: Real-time, label-free imaging of lymphocyte subsets

Abstract Background: Immune Cell Killing (ICK) Assay is pivotal in immunology and clinical research, uncovering the intricate connections between the immune system and diseases. Traditional ICK assays utilizing antibody staining for endpoint data generation pose challenges in capturing dynamic interactions. Moreover, antibody labeling for data quantification may compromise sensitivity, especially with low-affinity antibodies or a limited number of cells. The anticipation of label-free lymphocyte subset classification and real-time effector/target cell interaction analysis in one field of view is expected to provide more valuable insights than traditional ICK assays. Previous studies achieved 70-80% accuracy in image-based lymphocyte subset classification using digital holographic microscopy, light scattering, etc. but the cells’ condition during the cell sorting or sample preparation process may affect the lymphocyte subset status, resulting in real morphological discrepancies. Our approach focuses on directly sorting human PBMCs to enable label-free, dynamic interaction analysis of natural immune system responses in one field of view. Method: In this study, PBMC samples from 6 individuals were separated using standard-density gradient centrifugation and labeled with antibodies. Data were acquired using the Holotomographic Microscope HT-X1 (Tomocube Inc.). We employed Densenet 121 as the deep learning model architecture, considering the trade-off between memory consumption and performance. The cross-entropy loss function was utilized, and the AdamW optimizer was chosen for model parameter optimization. Input data consisted of 3D refractive index (RI) data for individual cells, each of sized (20, 54, 54). Individual cell labeling was performed using staining information. Results: An overall accuracy of 93.75% in Human PBMC subtype cell classification was achieved. In stage 1, an accuracy of 97.56% was demonstrated in classifying [CD14, CD15, Others]. Among the cells classified as "Others" in stage 2, [CD3, CD19, CD16&CD56] displayed an accuracy of 93.5%. In stage 3, classifying [CD4, CD8] within the CD3 subtype achieved an accuracy of 90.2%. This classification is presumably based on pattern recognition of the chromosomal landscape in holotomography images. Conclusion: Our research has successfully demonstrated the feasibility of real-time label-free lymphocyte subset classification. This approach enabled the classification of effector cells as live cells in ICK assay and the analysis of effector-target cell dynamic interactions. Further training in the classification of more detailed subtype cells and various cell death types will provide additional insights. The advancement of this technology is expected to play a pivotal role in disease prevention, treatment, vaccine development, medical research, and academic studies. Citation Format: Sanggeun Oh, Jaephil Do, Hyun-Seok Min, Dongmin Ryu, Wei sun Park. Advancing ICK assay: Real-time, label-free imaging of lymphocyte subsets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2530.

Image Processing Techniques for Improving Quality of 3D Profile in Digital Holographic Microscopy Using Deep Learning Algorithm.

Digital Holographic Microscopy (DHM) is a 3D imaging technology widely applied in biology, microelectronics, and medical research. However, the noise generated during the 3D imaging process can affect the accuracy of medical diagnoses. To solve this problem, we proposed several frequency domain filtering algorithms. However, the filtering algorithms we proposed have a limitation in that they can only be applied when the distance between the direct current (DC) spectrum and sidebands are sufficiently far. To address these limitations, among the proposed filtering algorithms, the HiVA algorithm and deep learning algorithm, which effectively filter by distinguishing between noise and detailed information of the object, are used to enable filtering regardless of the distance between the DC spectrum and sidebands. In this paper, a combination of deep learning technology and traditional image processing methods is proposed, aiming to reduce noise in 3D profile imaging using the Improved Denoising Diffusion Probabilistic Models (IDDPM) algorithm.

A dynamic study of VEGF-A siDOX-EVs trafficking through the in-vitro insert co-culture blood-brain barrier model by digital holographic microscopy.

Modeling the blood-brain barrier has long been a challenge for pharmacological studies. Up to the present, numerous attempts have been devoted to recapitulating the endothelial barrier in vitro to assess drug delivery vehicles' efficiency for brain disorders. In the current work, we presented a new approach for analyzing the morphometric parameters of the cells of an insert co-culture blood-brain barrier model using rat brain astrocytes, rat brain microvascular endothelial cells, and rat brain pericytes. This analytical approach could aid in getting further information on drug trafficking through the blood-brain barrier and its impact on the brain indirectly. In the current work, we cultured rat brain astrocytes, rat brain microvascular endothelial cells, and rat brain pericytes and then used an insert well to culture the cells in contact with each other to model the blood-brain barrier. Then, the morphometric parameters of the porous membrane of the insert well, as well as each cell type were imaged by digital holographic microscopy before and after cell seeding. At last, we performed folate conjugation on the surface of the EVs we have previously tested for glioma therapy in our previous work called VEGF-A siDOX-EVs and checked how the trafficking of EVs improves after folate conjugation as a clathrin-mediated delivery setup. the trafficking and passage of EVs were assessed by flowcytometry and morphometric analysis of the digital holographic microscopy holograms. Our results indicated that EVs successfully entered through the proposed endothelial barrier assessed by flow cytometry analysis and furthermore, folate conjugation significantly improved EV passage through the blood-brain barrier. Moreover, our results indicated that the VEGF-A siDOX-EVs insert cytotoxic impact on the cells of the bottom of the culture plate. folate-conjugation on the surface of EVs improves their trafficking through the blood-brain barrier and by using digital holographic microscopy analysis, we could directly assess the morphometric changes of the blood-brain barrier cells for pharmacological purposes as an easy, label-free, and real-time analysis.

Research Status and Progress on Non-Destructive Testing Methods for Defect Inspection of Micro-Electronic Packaging

Abstract In a highly competitive and demanding micro-electronics market, non-destructive testing (NDT) technology has been widely applied to defect detection and evaluation of micro-electronic packaging. However, the trend of micro-electronic packaging toward miniaturization, high-density, ultrathin, ultralight, and with small chip footprint, poses an urgent demand for novel NDT methods with high-resolution and large penetration depth, which is utilized for internal defect detection and identification of advanced complicated packages. The conventional NDT methods for micro-electronic packaging mainly include optical visual inspection, X-ray inspection, active infrared thermography, scanning acoustic microscopy (SAM), atomic force microscopy (AFM), laser Doppler vibration measuring technique, scanning SQUID microscopy (SSM), electrical impedance spectroscopy, scanning electron microscope (SEM), and so on. This paper aims to provide a review of addressing their basic principles, advantages, limitations, and application researches in the field of defect inspection of micro-electronic packaging. Moreover, in order to overcome the shortcomings of the existing NDT methods, this paper emphasizes a novel NDT approach, called hybrid ultrasonic-laser digital holographic microscopy (DHM) imaging inspection method, and discusses its basic principle, merits, key techniques, system construction, and experimental results in detail. When some key technical problems can be solved in further research, this method will become a potentially promising technique for defect detection and evaluation of advanced complicated packages.

All-optical dual module platform for motility-based functional scrutiny of microencapsulated probiotic bacteria.

Probiotic bacteria are widely used in pharmaceutics to offer health benefits. Microencapsulation is used to deliver probiotics into the human body. Capsules in the stomach have to keep bacteria constrained until release occurs in the intestine. Once outside, bacteria must maintain enough motility to reach the intestine walls. Here, we develop a platform based on two label-free optical modules for rapidly screening and ranking probiotic candidates in the laboratory. Bio-speckle dynamics assay tests the microencapsulation effectiveness by simulating the gastrointestinal transit. Then, a digital holographic microscope 3D-tracks their motility profiles at a single element level to rank the strains.

Guided wave resonance-based digital holographic microscopy for high-sensitivity monitoring of the refractive index.

Surface plasmon resonance holographic microscopy (SPRHM) has been employed to measure the refractive index but whose performance is generally limited by the metallic intrinsic loss. Herein we first, to our knowledge, utilize guided wave resonance (GWR) with low loss to realize the monitoring of the refractive index by integrating with digital holographic microscopy (DHM). By depositing a dielectric layer on a silver film, we observe a typical GWR in the dielectric layer with stronger field enhancement and higher sensitivity to the surrounding refractive index compared to the silver film-supported SPR, which agrees well with calculations. The innovative combination of the GWR and DHM contributes to the highly sensitive dynamic monitoring of the surrounding refractive index variation. Through the measurement with DHM, we found that the GWR presents an excellent sensitivity, which is 2.6 times higher than that of the SPR on the silver film. The results will pave a new pathway for digital holographic interferometry and its applications in environmental and biological detections.