Epi-illumination gradient light interference microscopy for imaging opaque structures

Non-invasive label-free imaging analysis pipeline for in situ characterization of 3D brain organoids

Brain organoids provide a unique opportunity to model organ development in a system similar to human organogenesis in vivo. Brain organoids thus hold great promise for drug screening and disease modeling. Conventional approaches to organoid characterization predominantly rely on molecular analysis methods, which are expensive, time-consuming, labor-intensive, and involve the destruction of the valuable three-dimensional (3D) architecture of the organoids. This reliance on end-point assays makes it challenging to assess cellular and subcellular events occurring during organoid development in their 3D context. As a result, the long developmental processes are not monitored nor assessed. The ability to perform non-invasive assays is critical for longitudinally assessing features of organoid development during culture. In this paper, we demonstrate a label-free high-content imaging approach for observing changes in organoid morphology and structural changes occurring at the cellular and subcellular level. Enabled by microfluidic-based culture of 3D cell systems and a novel 3D quantitative phase imaging method, we demonstrate the ability to perform non-destructive high-resolution quantitative image analysis of the organoid. The highlighted results demonstrated in this paper provide a new approach to performing live, non-destructive monitoring of organoid systems during culture.

Label-free, high-throughput holographic imaging to evaluate mammalian gametes and embryos†

Assisted reproduction is one of the significant tools to treat human infertility. Morphological assessment is the primary method to determine sperm and embryo viability during in vitro fertilization cycles. It has the advantage of being a quick, convenient, and inexpensive means of assessment. However, visual observation is of limited predictive value for early embryo morphology. It has led many to search for other imaging tools to assess the reproductive potential of a given embryo. The limitations of visual assessment apply to both humans and animals. One recent innovation in assisted reproduction technology imaging is interferometric phase microscopy, also known as holographic microscopy. Interferometric phase microscopy/quantitative phase imaging is the next likely progression of analytical microscopes for the assisted reproduction laboratory. The interferometric phase microscopy system analyzes waves produced by the light as it passes through the specimen observed. The microscope collects the light waves produced and uses the algorithm to create a hologram of the specimen. Recently, interferometric phase microscopy has been combined with quantitative phase imaging, which joins phase contrast microscopy with holographic microscopy. These microscopes collect light waves produced and use the algorithm to create a hologram of the specimen. Unlike other systems, interferometric phase microscopy can provide a quantitative digital image, and it can make 2D and 3D images of the samples. This review summarizes some newer and more promising quantitative phase imaging microscopy systems for evaluating gametes and embryos. Studies clearly show that quantitative phase imaging is superior to bright field microscopy-based evaluation methods when evaluating sperm and oocytes prior to IVF and embryos prior to transfer. However, further assessment of these systems for efficacy, reproducibility, cost-effectiveness, and embryo/gamete safety must take place before they are widely adopted.

Capturing cell morphology dynamics with high temporal resolution using single-shot quantitative phase gradient imaging

Significance

Label-free quantitative phase imaging can potentially measure cellular dynamics with minimal perturbation, motivating efforts to develop faster and more sensitive instrumentation. We characterize fast, single-shot quantitative phase gradient microscopy (ss-QPGM) that simultaneously acquires multiple polarization components required to reconstruct phase images. We integrate a computationally efficient least squares algorithm to provide real-time, video-rate imaging (up to 75   frames / s ). The developed instrument was used to observe changes in cellular morphology and correlate these to molecular measures commonly obtained by staining.

Aim

We aim to characterize a fast approach to ss-QPGM and record morphological changes in single-cell phase images. We also correlate these with biochemical changes indicating cell death using concurrently acquired fluorescence images.

Approach

Here, we examine nutrient deprivation and anticancer drug-induced cell death in two different breast cell lines, viz., M2 and MCF7. Our approach involves in-line measurements of ss-QPGM and fluorescence imaging of the cells biochemically labeled for viability.

Results

We validate the accuracy of the phase measurement using a USAF1951 pattern phase target. The ss-QPGM system resolves 912.3    lp / mm , and our analysis scheme accurately retrieves the phase with a high correlation coefficient ( ∼ 0.99 ), as measured by calibrated sample thicknesses. Analyzing the contrast in phase, we estimate the spatial resolution achievable to be 0.55    μ m for this microscope. ss-QPGM time-lapse live-cell imaging reveals multiple intracellular and morphological changes during biochemically induced cell death. Inferences from co-registered images of quantitative phase and fluorescence suggest the possibility of necrosis, which agrees with previous findings.

Conclusions

Label-free ss-QPGM with high-temporal resolution and high spatial fidelity is demonstrated. Its application for monitoring dynamic changes in live cells offers promising prospects.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part II

Significance

Quantitative phase imaging (QPI) is a non-invasive, label-free technique that provides intrinsic information about the sample under study. Such information includes the structure, function, and dynamics of the sample. QPI overcomes the limitations of conventional fluorescence microscopy in terms of phototoxicity to the sample and photobleaching of the fluorophore. As such, the application of QPI in estimating the three-dimensional (3D) structure and dynamics is well-suited for a range of samples from intracellular organelles to highly scattering multicellular samples while allowing for longer observation windows.

Aim

We aim to provide a comprehensive review of 3D QPI and related phase-based measurement techniques along with a discussion of methods for the estimation of sample dynamics.

Approach

We present information collected from 106 publications that cover the theoretical description of 3D light scattering and the implementation of related measurement techniques for the study of the structure and dynamics of the sample. We conclude with a discussion of the applications of the reviewed techniques in the biomedical field.

Results

QPI has been successfully applied to 3D sample imaging. The scattering-based contrast provides measurements of intrinsic quantities of the sample that are indicative of disease state, stage of growth, or overall dynamics.

Conclusions

We reviewed state-of-the-art QPI techniques for 3D imaging and dynamics estimation of biological samples. Both theoretical and experimental aspects of various techniques were discussed. We also presented the applications of the discussed techniques as applied to biomedicine and biology research.

Vibrational imaging of metabolites for improved microbial cell strains

Significance

Biomanufacturing utilizes modified microbial systems to sustainably produce commercially important biomolecules for use in agricultural, energy, food, material, and pharmaceutical industries. However, technological challenges related to non-destructive and high-throughput metabolite screening need to be addressed to fully unlock the potential of synthetic biology and sustainable biomanufacturing.

Aim

This perspective outlines current analytical screening tools used in industrial cell strain development programs and introduces label-free vibrational spectro-microscopy as an alternative contrast mechanism.

Approach

We provide an overview of the analytical instrumentation currently used in the "test" portion of the design, build, test, and learn cycle of synthetic biology. We then highlight recent progress in Raman scattering and infrared absorption imaging techniques, which have enabled improved molecular specificity and sensitivity.

Results

Recent developments in high-resolution chemical imaging methods allow for greater throughput without compromising the image contrast. We provide a roadmap of future work needed to support integration with microfluidics for rapid screening at the single-cell level.

Conclusions

Quantifying the net expression of metabolites allows for the identification of cells with metabolic pathways that result in increased biomolecule production, which is essential for improving the yield and reducing the cost of industrial biomanufacturing. Technological advancements in vibrational microscopy instrumentation will greatly benefit biofoundries as a complementary approach for non-destructive cell screening.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I

Significance

Quantitative phase imaging (QPI) techniques offer intrinsic information about the sample of interest in a label-free, noninvasive manner and have an enormous potential for wide biomedical applications with negligible perturbations to the natural state of the sample in vitro.

Aim

We aim to present an in-depth review of the scattering formulation of light-matter interactions as applied to biological samples such as cells and tissues, discuss the relevant quantitative phase measurement techniques, and present a summary of various reported applications.

Approach

We start with scattering theory and scattering properties of biological samples followed by an exploration of various microscopy configurations for 2D QPI for measurement of structure and dynamics.

Results

We reviewed 157 publications and presented a range of QPI techniques and discussed suitable applications for each. We also presented the theoretical frameworks for phase reconstruction associated with the discussed techniques and highlighted their domains of validity.

Conclusions

We provide detailed theoretical as well as system-level information for a wide range of QPI techniques. Our study can serve as a guideline for new researchers looking for an exhaustive literature review of QPI methods and relevant applications.

Multispectral Holographic Intensity and Phase Imaging of Semitransparent Ultrathin Films

In this paper, we demonstrate a novel optical characterization method for ultrathin semitransparent and absorbing materials through multispectral intensity and phase imaging. The method is based on a lateral-shearing interferometric microscopy (LIM) technique, where phase-shifting allows extraction of both the intensity and the phase of transmitted optical fields. To demonstrate the performance in characterizing semitransparent thin films, we fabricated and measured cupric oxide (CuO) seeded gold ultrathin metal films (UTMFs) with mass-equivalent thicknesses from 2 to 27 nm on fused silica substrates. The optical properties were modeled using multilayer thin film interference and a parametric model of their complex refractive indices. The UTMF samples were imaged in the spectral range from 475 to 750 nm using the proposed LIM technique, and the model parameters were fitted to the measured data in order to determine the respective complex refractive indices for varying thicknesses. Overall, by using the combined intensity and phase not only for imaging and quality control but also for determining the material properties, such as complex refractive indices, this technique demonstrates a high potential for the characterization of the optical properties, of (semi-) transparent thin films.

Non-Invasive Label-free Analysis Pipeline for In Situ Characterization of Differentiation in 3D Brain Organoid Models

Brain organoids provide a unique opportunity to model organ development in a system similar to human organogenesis in vivo. Brain organoids thus hold great promise for drug screening and disease modeling. Conventional approaches to organoid characterization predominantly rely on molecular analysis methods, which are expensive, time-consuming, labor-intensive, and involve the destruction of the valuable 3D architecture of the organoids. This reliance on end-point assays makes it challenging to assess cellular and subcellular events occurring during organoid development in their 3D context. As a result, the long developmental processes are not monitored nor assessed. The ability to perform non-invasive assays is critical for longitudinally assessing features of organoid development during culture. In this paper, we demonstrate a label-free high-content imaging approach for observing changes in organoid morphology and structural changes occurring at the cellular and subcellular level. Enabled by microfluidic-based culture of 3D cell systems and a novel 3D quantitative phase imaging method, we demonstrate the ability to perform non-destructive high-resolution imaging of the organoid. The highlighted results demonstrated in this paper provide a new approach to performing live, non-destructive monitoring of organoid systems during culture.

Towards ultrafast quantitative phase imaging via differentiable microscopy [Invited]

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse solvers, the throughput of QPM is currently limited by the pixel-rate of the image sensors. Complementarily, to improve throughput further, here we propose to acquire images in a compressed form so that more information can be transferred beyond the existing hardware bottleneck of the image sensor. To this end, we present a numerical simulation of a learnable optical compression-decompression framework that learns content-specific features. The proposed differentiable quantitative phase microscopy (∂-QPM) first uses learnable optical processors as image compressors. The intensity representations produced by these optical processors are then captured by the imaging sensor. Finally, a reconstruction network running on a computer decompresses the QPM images post aquisition. In numerical experiments, the proposed system achieves compression of × 64 while maintaining the SSIM of ∼0.90 and PSNR of ∼30 dB on cells. The results demonstrated by our experiments open up a new pathway to QPM systems that may provide unprecedented throughput improvements.

Fast Fourier ptychographic quantitative phase microscopy for in vitro label-free imaging

Quantitative phase microscopy (QPM) is indispensable in biomedical research due to its advantages in unlabeled transparent sample thickness quantification and obtaining refractive index information. Fourier ptychographic microscopy (FPM) is among the most promising QPM methods, incorporating multi-angle illumination and iterative phase recovery for high-resolution quantitative phase imaging (QPI) of large cell populations over a wide field of-view (FOV) in a single pass. However, FPM is limited by data redundancy and sequential acquisition strategies, resulting in low imaging efficiency, which in turn limits its real-time application in in vitro label-free imaging. Here, we report a fast QPM based on Fourier ptychography (FQP-FPM), which uses an optimized annular downsampling and parallel acquisition strategy to minimize the amount of data required in the front end and reduce the iteration time of the back-end algorithm (3.3% and 4.4% of conventional FPM, respectively). Theoretical and data redundancy analyses show that FQP-FPM can realize high-throughput quantitative phase reconstruction at thrice the resolution of the coherent diffraction limit by acquiring only ten raw images, providing a precondition for in vitro label-free real-time imaging. The FQP-FPM application was validated for various in vitro label-free live-cell imaging. Cell morphology and subcellular phenomena in different periods were observed with a synthetic aperture of 0.75 NA at a 10× FOV, demonstrating its advantages and application potential for fast high-throughput QPI.

Multi-harmonic structured illumination-based optical diffraction tomography

Imaging speed and spatial resolution are key factors in optical diffraction tomography (ODT), while they are mutually exclusive in 3D refractive index imaging. This paper presents a multi-harmonic structured illumination-based optical diffraction tomography (MHSI-ODT) to acquire 3D refractive index (RI) maps of transparent samples. MHSI-ODT utilizes a digital micromirror device (DMD) to generate structured illumination containing multiple harmonics. For each structured illumination orientation, four spherical spectral crowns are solved from five phase-shifted holograms, meaning that the acquisition of each spectral crown costs 1.25 raw images. Compared to conventional SI-ODT, which retrieves two spectral crowns from three phase-shifted raw images, MHSI-ODT enhances the imaging speed by 16.7% in 3D RI imaging. Meanwhile, MHSI-ODT exploits both the 1st-order and the 2nd-order harmonics; therefore, it has a better intensity utilization of structured illumination. We demonstrated the performance of MHSI-ODT by rendering the 3D RI distributions of 5 µm polystyrene (PS) microspheres and biological samples.

Roadmap on Label-Free Super-Resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles which need to be overcome to break the classical diffraction limit of the LFSR imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability which are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.

Mapping nanoscale topographic features in thick tissues with speckle diffraction tomography

Resolving three-dimensional morphological features in thick specimens remains a significant challenge for label-free imaging. We report a new speckle diffraction tomography (SDT) approach that can image thick biological specimens with ~500 nm lateral resolution and ~1 μm axial resolution in a reflection geometry. In SDT, multiple-scattering background is rejected through spatiotemporal gating provided by dynamic speckle-field interferometry, while depth-resolved refractive index maps are reconstructed by developing a comprehensive inverse-scattering model that also considers specimen-induced aberrations. Benefiting from the high-resolution and full-field quantitative imaging capabilities of SDT, we successfully imaged red blood cells and quantified their membrane fluctuations behind a turbid medium with a thickness of 2.8 scattering mean-free paths. Most importantly, we performed volumetric imaging of cornea inside an ex vivo rat eye and quantified its optical properties, including the mapping of nanoscale topographic features of Dua's and Descemet's membranes that had not been previously visualized.

Reflectional quantitative differential phase microscopy using polarized wavefront phase modulation

Quantitative phase microscopy (QPM), as a label-free and nondestructive technique, has been playing an indispensable tool in biomedical imaging and industrial inspection. Herein, we introduce a reflectional quantitative differential phase microscopy (termed RQDPM) based on polarized wavefront phase modulation and partially coherent full-aperture illumination, which has high spatial resolution and spatio-temporal phase sensitivity and is applicable to opaque surfaces and turbid biological specimens. RQDPM does not require additional polarized devices and can be easily switched from reflectional mode to transmission mode. In addition, RQDPM inherits the characteristic of high axial resolution of differential interference contrast microscope, thereby providing topography for opaque surfaces. We experimentally demonstrate the reflectional phase imaging ability of RQDPM with several samples: semiconductor wafer, thick biological tissues, red blood cells, and Hela cells. Furthermore, we dynamically monitor the flow state of microspheres in a self-built microfluidic channel by using RQDPM converted into the transmission mode.

Viewing life without labels under optical microscopes

Optical microscopes today have pushed the limits of speed, quality, and observable space in biological specimens revolutionizing how we view life today. Further, specific labeling of samples for imaging has provided insight into how life functions. This enabled label-based microscopy to percolate and integrate into mainstream life science research. However, the use of labelfree microscopy has been mostly limited, resulting in testing for bio-application but not bio-integration. To enable bio-integration, such microscopes need to be evaluated for their timeliness to answer biological questions uniquely and establish a long-term growth prospect. The article presents key label-free optical microscopes and discusses their integrative potential in life science research for the unperturbed analysis of biological samples.

Single-shot isotropic differential interference contrast microscopy

Differential interference contrast (DIC) microscopy allows high-contrast, low-phototoxicity, and label-free imaging of transparent biological objects, and has been applied in the field of cellular morphology, cell segmentation, particle tracking, optical measurement and others. Commercial DIC microscopy based on Nomarski or Wollaston prism resorts to the interference of two polarized waves with a lateral differential offset (shear) and axial phase shift (bias). However, the shear generated by these prisms is limited to the rectilinear direction, unfortunately resulting in anisotropic contrast imaging. Here we propose an ultracompact metasurface-assisted isotropic DIC (i-DIC) microscopy based on a grand original pattern of radial shear interferometry, that converts the rectilinear shear into rotationally symmetric along radial direction, enabling single-shot isotropic imaging capabilities. The i-DIC presents a complementary fusion of typical meta-optics, traditional microscopes and integrated optical system, and showcases the promising and synergetic advancements in edge detection, particle motion tracking, and label-free cellular imaging.

Quantitative phase gradient metrology using diffraction phase microscopy and deep learning

In quantitative phase microscopy, measurement of the phase gradient is an important problem for biological cell morphological studies. In this paper, we propose a method based on a deep learning approach that is capable of direct estimation of the phase gradient without the requirement of phase unwrapping and numerical differentiation operations. We show the robustness of the proposed method using numerical simulations under severe noise conditions. Further, we demonstrate the method's utility for imaging different biological cells using diffraction phase microscopy setup.

Artificial confocal microscopy for deep label-free imaging

Widefield microscopy of optically thick specimens typically features reduced contrast due to "spatial crosstalk", in which the signal at each point in the field of view is the result of a superposition from neighbouring points that are simultaneously illuminated. In 1955, Marvin Minsky proposed confocal microscopy as a solution to this problem. Today, laser scanning confocal fluorescence microscopy is broadly used due to its high depth resolution and sensitivity, but comes at the price of photobleaching, chemical, and photo-toxicity. Here, we present artificial confocal microscopy (ACM) to achieve confocal-level depth sectioning, sensitivity, and chemical specificity, on unlabeled specimens, nondestructively. We equipped a commercial laser scanning confocal instrument with a quantitative phase imaging module, which provides optical path-length maps of the specimen in the same field of view as the fluorescence channel. Using pairs of phase and fluorescence images, we trained a convolution neural network to translate the former into the latter. The training to infer a new tag is very practical as the input and ground truth data are intrinsically registered, and the data acquisition is automated. The ACM images present significantly stronger depth sectioning than the input (phase) images, enabling us to recover confocal-like tomographic volumes of microspheres, hippocampal neurons in culture, and 3D liver cancer spheroids. By training on nucleus-specific tags, ACM allows for segmenting individual nuclei within dense spheroids for both cell counting and volume measurements. In summary, ACM can provide quantitative, dynamic data, nondestructively from thick samples, while chemical specificity is recovered computationally.

ROCS microscopy with distinct zero-order blocking

Research in modern light microscopy continuously seeks to improve spatial and temporal resolution in combination with user-friendly, cost-effective imaging systems. Among different label-free imaging approaches, Rotating Coherent Scattering (ROCS) microscopy in darkfield mode achieves superior resolution and contrast without image reconstructions, which is especially helpful in life cell experiments. Here we demonstrate how to achieve 145 nm resolution with an amplitude transmission mask for spatial filtering. This mask blocks the reflected 0-th order focus at 12 distinct positions, thereby increasing the effective aperture for the light back-scattered from the object. We further show how angular correlation analysis between coherent raw images helps to estimate the information content from different illumination directions.

White blood cell detection, classification and analysis using phase imaging with computational specificity (PICS)

Treatment of blood smears with Wright's stain is one of the most helpful tools in detecting white blood cell abnormalities. However, to diagnose leukocyte disorders, a clinical pathologist must perform a tedious, manual process of locating and identifying individual cells. Furthermore, the staining procedure requires considerable preparation time and clinical infrastructure, which is incompatible with point-of-care diagnosis. Thus, rapid and automated evaluations of unlabeled blood smears are highly desirable. In this study, we used color spatial light interference microcopy (cSLIM), a highly sensitive quantitative phase imaging (QPI) technique, coupled with deep learning tools, to localize, classify and segment white blood cells (WBCs) in blood smears. The concept of combining QPI label-free data with AI for the purpose of extracting cellular specificity has recently been introduced in the context of fluorescence imaging as phase imaging with computational specificity (PICS). We employed AI models to first translate SLIM images into brightfield micrographs, then ran parallel tasks of locating and labelling cells using EfficientNet, which is an object detection model. Next, WBC binary masks were created using U-net, a convolutional neural network that performs precise segmentation. After training on digitally stained brightfield images of blood smears with WBCs, we achieved a mean average precision of 75% for localizing and classifying neutrophils, eosinophils, lymphocytes, and monocytes, and an average pixel-wise majority-voting F1 score of 80% for determining the cell class from semantic segmentation maps. Therefore, PICS renders and analyzes synthetically stained blood smears rapidly, at a reduced cost of sample preparation, providing quantitative clinical information.

Label-free single-shot imaging with on-axis phase-shifting holographic reflectance quantitative phase microscopy

Quantitative phase microscopy (QPM) has been emerged as an indispensable diagnostic and characterization tool in biomedical imaging with its characteristic nature of label-free, noninvasive, and real time imaging modality. The integration of holography to the conventional microscopy opens new advancements in QPM featuring high-resolution and quantitative three-dimensional image reconstruction. However, the holography schemes suffer in space-bandwidth and time-bandwidth issues in the off-axis and phase-shifting configuration, respectively. Here, we introduce an on-axis phase-shifting holography based QPM system with single-shot imaging capability. The technique utilizes the Fizeau interferometry scheme in combination with polarization phase-shifting and space-division multiplexing to achieve the single-shot recording of the multiple phase-shifted holograms. Moreover, the high-speed imaging capability with instantaneous recording of spatially phase shifted holograms offers the flexible utilization of the approach in dynamic quantitative phase imaging with robust phase stability. We experimentally demonstrated the validity of the approach by quantitative phase imaging and depth-resolved imaging of paramecium cells. Furthermore, the technique is applied to the phase imaging and quantitative parameter estimation of red blood cells. This integration of a Fizeau-based phase-shifting scheme to the optical microscopy enables a simple and robust tool for the investigations of engineered and biological specimen with real-time quantitative analysis.

Circadian Volume Changes in Hippocampal Glia Studied by Label-Free Interferometric Imaging

Complex brain functions, including learning and memory, arise in part from the modulatory role of astrocytes on neuronal circuits. Functionally, the dentate gyrus (DG) exhibits differences in the acquisition of long-term potentiation (LTP) between day and night. We hypothesize that the dynamic nature of astrocyte morphology plays an important role in the functional circuitry of hippocampal learning and memory, specifically in the DG. Standard microscopy techniques, such as differential interference contrast (DIC), present insufficient contrast for detecting changes in astrocyte structure and function and are unable to inform on the intrinsic structure of the sample in a quantitative manner. Recently, gradient light interference microscopy (GLIM) has been developed to upgrade a DIC microscope with quantitative capabilities such as single-cell dry mass and volume characterization. Here, we present a methodology for combining GLIM and electrophysiology to quantify the astrocyte morphological behavior over the day-night cycle. Colocalized measurements of GLIM and fluorescence allowed us to quantify the dry masses and volumes of hundreds of astrocytes. Our results indicate that, on average, there is a 25% cell volume reduction during the nocturnal cycle. Remarkably, this cell volume change takes place at constant dry mass, which suggests that the volume regulation occurs primarily through aqueous medium exchange with the environment.

Reflectional quantitative phase-contrast microscopy (RQPCM) with annular epi-illumination

Quantitative phase microscopy (QPM) is a label-free microscopic technique that exploits the phase of a wave passing through a sample; hence, it has been applied to many fields, including biomedical research and industrial inspection. However, the high spatiotemporal resolution imaging of reflective samples still challenges conventional transmission QPM. In this paper, we propose reflectional quantitative phase-contrast microscopy based on annular epi-illumination of light-emitting diodes. The unscattered wave from the sample is successively phase-retarded by 0, π/2, π, and 3π/2 through a spatial light modulator, and high-resolution phase-contrast images are obtained, revealing the finer structure or three-dimensional tomography of reflective samples. With this system, we have quantitatively obtained the contour of tissue slices and silicon semiconductor wafers. We believe that the proposed system will be very helpful for the high-resolution imaging of industrial devices and biomedical dynamics.

Cell Cycle Stage Classification Using Phase Imaging with Computational Specificity

Traditional methods for cell cycle stage classification rely heavily on fluorescence microscopy to monitor nuclear dynamics. These methods inevitably face the typical phototoxicity and photobleaching limitations of fluorescence imaging. Here, we present a cell cycle detection workflow using the principle of phase imaging with computational specificity (PICS). The proposed method uses neural networks to extract cell cycle-dependent features from quantitative phase imaging (QPI) measurements directly. Our results indicate that this approach attains very good accuracy in classifying live cells into G1, S, and G2/M stages, respectively. We also demonstrate that the proposed method can be applied to study single-cell dynamics within the cell cycle as well as cell population distribution across different stages of the cell cycle. We envision that the proposed method can become a nondestructive tool to analyze cell cycle progression in fields ranging from cell biology to biopharma applications.

100 Hz ROCS microscopy correlated with fluorescence reveals cellular dynamics on different spatiotemporal scales

Fluorescence techniques dominate the field of live-cell microscopy, but bleaching and motion blur from too long integration times limit dynamic investigations of small objects. High contrast, label-free life-cell imaging of thousands of acquisitions at 160 nm resolution and 100 Hz is possible by Rotating Coherent Scattering (ROCS) microscopy, where intensity speckle patterns from all azimuthal illumination directions are added up within 10 ms. In combination with fluorescence, we demonstrate the performance of improved Total Internal Reflection (TIR)-ROCS with variable illumination including timescale decomposition and activity mapping at five different examples: millisecond reorganization of macrophage actin cortex structures, fast degranulation and pore opening in mast cells, nanotube dynamics between cardiomyocytes and fibroblasts, thermal noise driven binding behavior of virus-sized particles at cells, and, bacterial lectin dynamics at the cortex of lung cells. Using analysis methods we present here, we decipher how motion blur hides cellular structures and how slow structure motions cover decisive fast motions.

Label-free imaging of intracellular organelle dynamics using flat-fielding quantitative phase contrast microscopy (FF-QPCM)

Panoramic and long-term observation of nanosized organelle dynamics and interactions with high spatiotemporal resolution still hold great challenge for current imaging platforms. In this study, we propose a live-organelle imaging platform, where a flat-fielding quantitative phase contrast microscope (FF-QPCM) visualizes all the membrane-bound subcellular organelles, and an intermittent fluorescence channel assists in specific organelle identification. FF-QPCM features a high spatiotemporal resolution of 245 nm and 250 Hz and strong immunity against external disturbance. Thus, we could investigate several important dynamic processes of intracellular organelles from direct perspectives, including chromosome duplication in mitosis, mitochondrial fusion and fission, filaments, and vesicles' morphologies in apoptosis. Of note, we have captured, for the first time, a new type of mitochondrial fission (entitled mitochondrial disintegration), the generation and fusion process of vesicle-like organelles, as well as the mitochondrial vacuolization during necrosis. All these results bring us new insights into spatiotemporal dynamics and interactions among organelles, and hence aid us in understanding the real behaviors and functional implications of the organelles in cellular activities.

Live-dead assay on unlabeled cells using phase imaging with computational specificity

Existing approaches to evaluate cell viability involve cell staining with chemical reagents. However, the step of exogenous staining makes these methods undesirable for rapid, nondestructive, and long-term investigation. Here, we present an instantaneous viability assessment of unlabeled cells using phase imaging with computation specificity. This concept utilizes deep learning techniques to compute viability markers associated with the specimen measured by label-free quantitative phase imaging. Demonstrated on different live cell cultures, the proposed method reports approximately 95% accuracy in identifying live and dead cells. The evolution of the cell dry mass and nucleus area for the labeled and unlabeled populations reveal that the chemical reagents decrease viability. The nondestructive approach presented here may find a broad range of applications, from monitoring the production of biopharmaceuticals to assessing the effectiveness of cancer treatments.

Common methods for characterising cell viability involve cell staining with chemical reagents. Here the authors report a method for cell viability assessment that does not require labelling; this uses quantitative phase imaging combined with deep learning.

Local Surface Chemistry Dynamically Monitored by Quantitative Phase Microscopy

Surface modification by photo grafting constitutes an interesting strategy to prepare functional surfaces. Precision applications, however, demand quantitative methods able to monitor and control the amount and distribution of surface modifications, which is hard to achieve, particularly in operando conditions. In this paper, a label-free, cost-effective, all-optical method based on wavefront sensing which is able to quantitatively track the evolution of grafted layers in real-time, is presented. By positioning a simple thin diffuser in the close vicinity of a camera, the thickness of grafted patterns is directly evaluated with sub-nanometric sensitivity and diffraction-limited lateral resolution. By performing an in-depth kinetic analysis of the local modification of an inert substrate (glass cover slips) through photografting of arydiazonium salts, different growth regimes are characterized and several parameters are estimated, such as the grafting efficiency, density and the apparent refractive index distribution of the resulting grafted layers. Both focused and widefield-grafting can be quantitatively monitored in real time, providing valuable guidelines to maximize functionalization efficiency. The association of a well-characterized versatile photografting reaction with the proposed flexible and sensitive monitoring strategy enables functional surfaces to be prepared, and puts surface micro- to submicro-structuration within the reach of most laboratories.

Synthetic aperture interference light (SAIL) microscopy for high-throughput label-free imaging

Quantitative phase imaging (QPI) is a valuable label-free modality that has gained significant interest due to its wide potentials, from basic biology to clinical applications. Most existing QPI systems measure microscopic objects via interferometry or nonlinear iterative phase reconstructions from intensity measurements. However, all imaging systems compromise spatial resolution for the field of view and vice versa, i.e., suffer from a limited space bandwidth product. Current solutions to this problem involve computational phase retrieval algorithms, which are time-consuming and often suffer from convergence problems. In this article, we presented synthetic aperture interference light (SAIL) microscopy as a solution for high-resolution, wide field of view QPI. The proposed approach employs low-coherence interferometry to directly measure the optical phase delay under different illumination angles and produces large space-bandwidth product label-free imaging. We validate the performance of SAIL on standard samples and illustrate the biomedical applications on various specimens: pathology slides, entire insects, and dynamic live cells in large cultures. The reconstructed images have a synthetic numeric aperture of 0.45 and a field of view of 2.6 × 2.6 mm2. Due to its direct measurement of the phase information, SAIL microscopy does not require long computational time, eliminates data redundancy, and always converges.

Diffraction as scattering under the Born approximation

Light diffraction at an aperture is a basic problem that has generated a tremendous amount of interest in optics. Some of the most significant diffraction results are the Fresnel-Kirchhoff and Rayleigh-Sommerfeld formulas. These theories are based on solving the wave equation using Green's theorem and result in slightly different expressions depending on the particular boundary conditions employed. In this paper, we show that the diffraction by a thin screen, which includes apertures, gratings, transparencies etc, can be treated more generally as a particular case of scattering. Furthermore, applying the first order Born approximation to 2D objects, we obtain a general diffraction formula, without angular approximations. Finally, our result, which contains no obliquity factor, is consistent with the 3D theory of scattering. We discuss several common approximations and place our results in the context of existing theories.

Monitoring reactivation of latent HIV by label-free gradient light interference microscopy

Human immunodeficiency virus (HIV) can infect cells and take a quiescent and nonexpressive state called latency. In this study, we report insights provided by label-free, gradient light interference microscopy (GLIM) about the changes in dry mass, diameter, and dry mass density associated with infected cells that occur upon reactivation. We discovered that the mean cell dry mass and mean diameter of latently infected cells treated with reactivating drug, TNF-α, are higher for latent cells that reactivate than those of the cells that did not reactivate. Cells with mean dry mass and diameter less than approximately 10 pg and 8 μm, respectively, remain exclusively in the latent state. Also, cells with mean dry mass greater than approximately 28-30 pg and mean diameter greater than 11–12 μm have a higher probability of reactivating. This study is significant as it presents a new label-free approach to quantify latent reactivation of a virus in single cells.

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GLIM imaging reveals differences between latent and reactivated HIV in JLat cells

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Cells with reactivated HIV have higher dry mass and diameter

Single-shot quantitative phase imaging as an extension of differential interference contrast microscopy

Various studies have been conducted to obtain quantitative phase information based on differential interference contrast (DIC) microscopy. As one such attempt, we propose in this study a single-shot quantitative phase imaging (QPI) method by combining two developments. First, an add-on optical system to a commercialized DIC microscope was developed to perform quantitative phase gradient imaging (QPGI) with single image acquisition using a polarization camera. Second, an algorithm was formulated to reconstitute QPI from the obtained QPGI by reducing linear artifacts, which arise in simply integrated QPGI images. To demonstrate the applicability of the developed system in cell biology, the system was used to measure various cell lines and compared with fluorescence microscopy images of the same field of view. Consistent with previous studies, nucleoli and lipid droplets can be imaged by the system with greater optical path lengths (OPL). The results also implied that combining fluorescence microscopy and the developed system might be more informative for cell biology research than using these methods individually. Exploiting the single-shot performance of the developed system, time-lapse imaging was also conducted to visualize the dynamics of intracellular granules in monocyte-/macrophage-like cells. Our proposed approach may accelerate the implementation of QPI in standard biomedical laboratories.

Label-free screening of brain tissue myelin content using phase imaging with computational specificity (PICS)

Inadequate myelination in the central nervous system is associated with neurodevelopmental complications. Thus, quantitative, high spatial resolution measurements of myelin levels are highly desirable. We used spatial light interference microcopy (SLIM), a highly sensitive quantitative phase imaging (QPI) technique, to correlate the dry mass content of myelin in piglet brain tissue with dietary changes and gestational size. We combined SLIM micrographs with an artificial intelligence (AI) classifying model that allows us to discern subtle disparities in myelin distributions with high accuracy. This concept of combining QPI label-free data with AI for the purpose of extracting molecular specificity has recently been introduced by our laboratory as phase imaging with computational specificity. Training on 8000 SLIM images of piglet brain tissue with the 71-layer transfer learning model Xception, we created a two-parameter classification to differentiate gestational size and diet type with an accuracy of 82% and 80%, respectively. To our knowledge, this type of evaluation is impossible to perform by an expert pathologist or other techniques.

Spatial light interference microscopy: principle and applications to biomedicine

In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-shifting interferometer, built onto a phase-contrast microscope, with white-light illumination. As one of the most sensitive quantitative phase imaging (QPI) methods, SLIM allows for speckle-free phase reconstruction with sub-nanometer path-length stability. We first review image formation in QPI, scattering, and full-field methods. Then, we outline SLIM imaging from theory and instrumentation to diffraction tomography. Zernike's phase-contrast microscopy, phase retrieval in SLIM, and halo removal algorithms are discussed. Next, we discuss the requirements for operation, with a focus on software developed in-house for SLIM that enables high-throughput acquisition, whole slide scanning, mosaic tile registration, and imaging with a color camera. We introduce two methods for solving the inverse problem using SLIM, white-light tomography, and Wolf phase tomography. Lastly, we review the applications of SLIM in basic science and clinical studies. SLIM can study cell dynamics, cell growth and proliferation, cell migration, mass transport, etc. In clinical settings, SLIM can assist with cancer studies, reproductive technology, blood testing, etc. Finally, we review an emerging trend, where SLIM imaging in conjunction with artificial intelligence brings computational specificity and, in turn, offers new solutions to outstanding challenges in cell biology and pathology.

Multiscale Assay of Unlabeled Neurite Dynamics Using Phase Imaging with Computational Specificity

Primary neuronal cultures have been widely used to study neuronal morphology, neurophysiology, neurodegenerative processes, and molecular mechanism of synaptic plasticity underlying learning and memory. However, the unique behavioral properties of neurons make them challenging to study, with phenotypic differences expressed as subtle changes in neuronal arborization rather than easy-to-assay features such as cell count. The need to analyze morphology, growth, and intracellular transport has motivated the development of increasingly sophisticated microscopes and image analysis techniques. Due to its high-contrast, high-specificity output, many assays rely on confocal fluorescence microscopy, genetic methods, or antibody staining techniques. These approaches often limit the ability to measure quantitatively dynamic activity such as intracellular transport and growth. In this work, we describe a method for label-free live-cell cell imaging with antibody staining specificity by estimating the associated fluorescence signals via quantitative phase imaging and deep convolutional neural networks. This computationally inferred fluorescence image is then used to generate a semantic segmentation map, annotating subcellular compartments of live unlabeled neural cultures. These synthetic fluorescence maps were further applied to study the time-lapse development of hippocampal neurons, highlighting the relationships between the cellular dry mass production and the dynamic transport activity within the nucleus and neurites. Our implementation provides a high-throughput strategy to analyze neural network arborization dynamically, with high specificity and without the typical phototoxicity and photobleaching limitations associated with fluorescent markers.

Fast photothermal spatial light modulation for quantitative phase imaging at the nanoscale

Spatial light modulators have become an essential tool for advanced microscopy, enabling breakthroughs in 3D, phase, and super-resolution imaging. However, continuous spatial-light modulation that is capable of capturing sub-millisecond microscopic motion without diffraction artifacts and polarization dependence is challenging. Here we present a photothermal spatial light modulator (PT-SLM) enabling fast phase imaging for nanoscopic 3D reconstruction. The PT-SLM can generate a step-like wavefront change, free of diffraction artifacts, with a high transmittance and a modulation efficiency independent of light polarization. We achieve a phase-shift > π and a response time as short as 70 µs with a theoretical limit in the sub microsecond range. We used the PT-SLM to perform quantitative phase imaging of sub-diffractional species to decipher the 3D nanoscopic displacement of microtubules and study the trajectory of a diffusive microtubule-associated protein, providing insights into the mechanism of protein navigation through a complex microtubule network.

Computational interference microscopy enabled by deep learning

Quantitative phase imaging (QPI) has been widely applied in characterizing cells and tissues. Spatial light interference microscopy (SLIM) is a highly sensitive QPI method due to its partially coherent illumination and common path interferometry geometry. However, SLIM's acquisition rate is limited because of the four-frame phase-shifting scheme. On the other hand, off-axis methods such as diffraction phase microscopy (DPM) allow for single-shot QPI. However, the laser-based DPM system is plagued by spatial noise due to speckles and multiple reflections. In a parallel development, deep learning was proven valuable in the field of bioimaging, especially due to its ability to translate one form of contrast into another. Here, we propose using deep learning to produce synthetic, SLIM-quality, and high-sensitivity phase maps from DPM using single-shot images as the input. We used an inverted microscope with its two ports connected to the DPM and SLIM modules such that we have access to the two types of images on the same field of view. We constructed a deep learning model based on U-net and trained on over 1000 pairs of DPM and SLIM images. The model learned to remove the speckles in laser DPM and overcame the background phase noise in both the test set and new data. The average peak signal-to-noise ratio, Pearson correlation coefficient, and structural similarity index measure were 29.97, 0.79, and 0.82 for the test dataset. Furthermore, we implemented the neural network inference into the live acquisition software, which now allows a DPM user to observe in real-time an extremely low-noise phase image. We demonstrated this principle of computational interference microscopy imaging using blood smears, as they contain both erythrocytes and leukocytes, under static and dynamic conditions.

High-resolution impedance mapping using electrically activated quantitative phase imaging

Retrieving electrical impedance maps at the nanoscale rapidly via nondestructive inspection with a high signal-to-noise ratio is an unmet need, likely to impact various applications from biomedicine to energy conversion. In this study, we develop a multimodal functional imaging instrument that is characterized by the dual capability of impedance mapping and phase quantitation, high spatial resolution, and low temporal noise. To achieve this, we advance a quantitative phase imaging system, referred to as epi-magnified image spatial spectrum microscopy combined with electrical actuation, to provide complementary maps of the optical path and electrical impedance. We demonstrate our system with high-resolution maps of optical path differences and electrical impedance variations that can distinguish nanosized, semi-transparent, structured coatings involving two materials with relatively similar electrical properties. We map heterogeneous interfaces corresponding to an indium tin oxide layer exposed by holes with diameters as small as ~550 nm in a titanium (dioxide) over-layer deposited on a glass support. We show that electrical modulation during the phase imaging of a macro-electrode is decisive for retrieving electrical impedance distributions with submicron spatial resolution and beyond the limitations of electrode-based technologies (surface or scanning technologies). The findings, which are substantiated by a theoretical model that fits the experimental data very well enable achieving electro-optical maps with high spatial and temporal resolutions. The virtues and limitations of the novel optoelectrochemical method that provides grounds for a wider range of electrically modulated optical methods for measuring the electric field locally are critically discussed.

Quantitative 3D refractive index tomography of opaque samples in epi-mode

Three-dimensional (3D) refractive index (RI) tomography has recently become an exciting new tool for biological studies. However, its limitation to (1) thin samples resulting from a need of transmissive illumination and (2) small fields of view (typically ~50 μm × 50 μm) has hindered its utility in broader biomedical applications. In this work, we demonstrate 3D RI tomography with a large field of view in opaque, arbitrarily thick scattering samples (unsuitable for imaging with conventional transmissive tomographic techniques) with a penetration depth of ca. one mean free scattering path length (~100 μm in tissue) using a simple, low-cost microscope system with epi-illumination. This approach leverages a solution to the inverse scattering problem via the general non-paraxial 3D optical transfer function of our quantitative oblique back-illumination microscopy (qOBM) optical system. A theoretical analysis is presented along with simulations and experimental validations using polystyrene beads, and rat and human thick brain tissues. This work has significant implications for the investigation of optically thick, semi-infinite samples in a non-invasive and label-free manner. This unique 3D qOBM approach can extend the utility of 3D RI tomography for translational and clinical medicine.

Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments

Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy's utility. Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast into another. We present phase imaging with computational specificity (PICS), a combination of quantitative phase imaging and AI, which provides information about unlabeled live cells with high specificity. Our imaging system allows for automatic training, while inference is built into the acquisition software and runs in real-time. Applying the computed fluorescence maps back to the quantitative phase imaging (QPI) data, we measured the growth of both nuclei and cytoplasm independently, over many days, without loss of viability. Using a QPI method that suppresses multiple scattering, we measured the dry mass content of individual cell nuclei within spheroids. In its current implementation, PICS offers a versatile quantitative technique for continuous simultaneous monitoring of individual cellular components in biological applications where long-term label-free imaging is desirable.

Quantifying myelin content in brain tissue using color Spatial Light Interference Microscopy (cSLIM)

Deficient myelination of the brain is associated with neurodevelopmental delays, particularly in high-risk infants, such as those born small in relation to their gestational age (SGA). New methods are needed to further study this condition. Here, we employ Color Spatial Light Interference Microscopy (cSLIM), which uses a brightfield objective and RGB camera to generate pathlength-maps with nanoscale sensitivity in conjunction with a regular brightfield image. Using tissue sections stained with Luxol Fast Blue, the myelin structures were segmented from a brightfield image. Using a binary mask, those portions were quantitatively analyzed in the corresponding phase maps. We first used the CLARITY method to remove tissue lipids and validate the sensitivity of cSLIM to lipid content. We then applied cSLIM to brain histology slices. These specimens are from a previous MRI study, which demonstrated that appropriate for gestational age (AGA) piglets have increased internal capsule myelination (ICM) compared to small for gestational age (SGA) piglets and that a hydrolyzed fat diet improved ICM in both. The identity of samples was blinded until after statistical analyses.

Matrix Softness-Mediated 3D Zebrafish Hepatocyte Modulates Response to Endocrine Disrupting Chemicals

Endocrine disrupting chemicals (EDC) include synthetic compounds that mimic the structure or function of natural hormones. While most studies utilize live embryos or primary cells from adult fish, these cells rapidly lose functionality when cultured on plastic or glass substrates coated with extracellular matrix proteins. This study hypothesizes that the softness of a matrix with adhered fish cells can regulate the intercellular organization and physiological function of engineered hepatoids during EDC exposure. We scrutinized this hypothesis by culturing zebrafish hepatocytes (ZF-L) on collagen-based hydrogels with controlled elastic moduli by examining morphology, urea production, and intracellular oxidative stress of hepatoids exposed to 17β-estradiol. Interestingly, the softer gel drove cells to form a cell sheet with a canaliculi-like structure compared to its stiffer gel counterpart. The hepatoids cultured on the softer gel exhibited more active urea production upon exposure to 17β-estradiol and displayed faster recovery of intracellular reactive oxygen species level confirmed by gradient light interference microscopy (GLIM), a live-cell imaging technique. These results are broadly useful to improve screening and understanding of potential EDC impacts on aquatic organisms and human health.

Smart filtering of phase residues in noisy wrapped holograms

Phase unwrapping is one of the major challenges in multiple branches of science that extract three-dimensional information of objects from wrapped signals. In several applications, it is important to extract the unwrapped information with minimal signal resolution degradation. However, most of the denoising techniques for unwrapping are designed to operate on the entire phase map to remove a limited number of phase residues, and therefore they significantly degrade critical information contained in the image. In this paper, we present a novel, smart, and automatic filtering technique for locally minimizing the number of phase residues in noisy wrapped holograms, based on the phasor average filtering (PAF) of patches around each residue point. Both patch sizes and PAF filters are increased in an iterative algorithm to minimize the number of residues and locally restrict the artifacts caused by filtering to the pixels around the residue pixels. Then, the improved wrapped phase can be unwrapped using a simple phase unwrapping technique. The feasibility of our method is confirmed by filtering, unwrapping, and enhancing the quality of a noisy hologram of neurons; the intensity distribution of the spatial frequencies demonstrates a 40-fold improvement, with respect to previous techniques, in preserving the higher frequencies.

Network science characteristics of brain-derived neuronal cultures deciphered from quantitative phase imaging data

Understanding the mechanisms by which neurons create or suppress connections to enable communication in brain-derived neuronal cultures can inform how learning, cognition and creative behavior emerge. While prior studies have shown that neuronal cultures possess self-organizing criticality properties, we further demonstrate that in vitro brain-derived neuronal cultures exhibit a self-optimization phenomenon. More precisely, we analyze the multiscale neural growth data obtained from label-free quantitative microscopic imaging experiments and reconstruct the in vitro neuronal culture networks (microscale) and neuronal culture cluster networks (mesoscale). We investigate the structure and evolution of neuronal culture networks and neuronal culture cluster networks by estimating the importance of each network node and their information flow. By analyzing the degree-, closeness-, and betweenness-centrality, the node-to-node degree distribution (informing on neuronal interconnection phenomena), the clustering coefficient/transitivity (assessing the “small-world” properties), and the multifractal spectrum, we demonstrate that murine neurons exhibit self-optimizing behavior over time with topological characteristics distinct from existing complex network models. The time-evolving interconnection among murine neurons optimizes the network information flow, network robustness, and self-organization degree. These findings have complex implications for modeling neuronal cultures and potentially on how to design biological inspired artificial intelligence.

Harmonic optical tomography of nonlinear structures

Second-harmonic generation microscopy is a valuable label-free modality for imaging non-centrosymmetric structures and has important biomedical applications from live-cell imaging to cancer diagnosis. Conventional second-harmonic generation microscopy measures intensity signals that originate from tightly focused laser beams, preventing researchers from solving the scattering inverse problem for second-order nonlinear materials. Here, we present harmonic optical tomography (HOT) as a novel modality for imaging microscopic, nonlinear and inhomogeneous objects. The HOT principle of operation relies on inter-ferometrically measuring the complex harmonic field and using a scattering inverse model to reconstruct the three-dimensional distribution of harmonophores. HOT enables strong axial sectioning via the momentum conservation of spatially and temporally broadband fields. We illustrate the HOT operation with experiments and reconstructions on a beta-barium borate crystal and various biological specimens. Although our results involve second-order nonlinear materials, we show that this approach applies to any coherent nonlinear process.

Imaging human blood cells in vivo with oblique back-illumination capillaroscopy

We present a non-invasive, label-free method of imaging blood cells flowing through human capillaries in vivo using oblique back-illumination capillaroscopy (OBC). Green light illumination allows simultaneous phase and absorption contrast, enhancing the ability to distinguish red and white blood cells. Single-sided illumination through the objective lens enables 200 Hz imaging with close illumination-detection separation and a simplified setup. Phase contrast is optimized when the illumination axis is offset from the detection axis by approximately 225 µm when imaging ∼80 µm deep in phantoms and human ventral tongue. We demonstrate high-speed imaging of individual red blood cells, white blood cells with sub-cellular detail, and platelets flowing through capillaries and vessels in human tongue. A custom pneumatic cap placed over the objective lens stabilizes the field of view, enabling longitudinal imaging of a single capillary for up to seven minutes. We present high-quality images of blood cells in individuals with Fitzpatrick skin phototypes II, IV, and VI, showing that the technique is robust to high peripheral melanin concentration. The signal quality, speed, simplicity, and robustness of this approach underscores its potential for non-invasive blood cell counting.

Inverse scattering for reflection intensity phase microscopy

Reflection phase imaging provides label-free, high-resolution characterization of biological samples, typically using interferometric-based techniques. Here, we investigate reflection phase microscopy from intensity-only measurements under diverse illumination. We evaluate the forward and inverse scattering model based on the first Born approximation for imaging scattering objects above a glass slide. Under this design, the measured field combines linear forward-scattering and height-dependent nonlinear back-scattering from the object that complicates object phase recovery. Using only the forward-scattering, we derive a linear inverse scattering model and evaluate this model's validity range in simulation and experiment using a standard reflection microscope modified with a programmable light source. Our method provides enhanced contrast of thin, weakly scattering samples that complement transmission techniques. This model provides a promising development for creating simplified intensity-based reflection quantitative phase imaging systems easily adoptable for biological research.