This PDF file contains the front matter associated with SPIE Proceedings Volume 12852, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Existing super-resolution imaging technology relies on rigid and bulky systems, which limits its application in narrow space. Endoscopy based on multimode fibers (MMF) has emerged as a significant solution for in vivo imaging. There is a high requirement to observe samples inside the lumen of the body simultaneously break through the diffraction limit. We propose the frequency-shift mechanism for universal super-resolution imaging with light-field encoded modulation. In this paper, we demonstrate our method for a single MMF in vivo imaging at subcellular resolution through light-field encoded, which can also ensure stable imaging under various operating conditions.

Adding AC electrical modulation to quantitative phase imaging (QPI) provides label-free, high-resolution images of the sample's optical path and electrical impedance. These maps reveal the distribution of the refractive index and conductivity, as complementary intrinsic parameters and imaging contrast elements of a (bio)sample. We measured the optical response of biological cells and nanopatterned surfaces upon electrical excitation at several AC frequencies. While previously we limited the analysis to the distribution of the phase-amplitude at the frequency of the applied AC field, we now extend the study to encompass the map of the AC modulated reflectivity. Specifically, we used magnified image spatial spectrum (MISS) microscopy to study the distribution of both electrical and optical parameters of a nanopatterned surface, and epi-illumination gradient light interference microscopy (epi-GLIM) for imaging cells adhered on a transparent electrode. We demonstrate the complementarity of the AC modulated phase and reflectivity versus their DC counterparts (when not applying an AC field) and discuss the advantages and limitations of the selected QPI methods concerning AC actuation. While MISS is a high-speed sensitive laser-based method, epi-GLIM combines phase shifting and white light interferometry. This multimodal study highlights new capabilities for gauging both electrical and optical hyper-structures of a sample (i.e., biological cell) and their dynamics in response to excitation, including exposure to drugs (antimicrobial/ antitumoral). Time-lapse access to cellular electro-optical fingerprints is prone to provide a new type of phenotypic approach, at both single-cell and population levels, likely to boost drug susceptibility/resistance testing assays based on lengthy microbiological methods.

Light-matter interactions play essential roles in realizing a new generation of nanoscale imaging to overcome traditional trade-offs between spatial resolution and time capabilities. By harnessing engineered nanophotonic materials, scattered light can be shaped to enhance light matter interactions for nanoscale bioimaging. We achieved nanoscale bioimaging with record long time capabilities. Long time nanoscopy has the potential to unlock a wide range of new dynamical studies and insights in assembly, organization and pattern formation in biological and material systems, where nanoscopic rearrangements drive group-level movements at the macroscale over time.

Fast, 3D imaging of living cells is a vital tool for studying complex biological processes. However, current fluorescence and phase imaging techniques either achieve maximum volumetric frame rates of less than 1 kHz or do not provide true 3D information in complex environments. While this is sufficient in many biological contexts, it is not fast enough to reveal e.g. the motion of cilia which beat at 100 Hz during swimming of some protists. Achieving kilohertz rate, true 3D volumetric imaging is an unmet challenge which would shed new light on this and other previously inaccessible regimes. To meet this challenge, we develop an optical diffraction tomography (ODT) instrument which utilizes a novel pattern generation scheme to overcome existing limitations to multiplexing, and achieves kilohertz volumetric frame rate 3D imaging. This approach adapts ODT, which has most often been considered in a biomedical context, to the unique requirements of biophysics and soft matter experiments. We construct ODT patterns using a technique we refer to as Fourier pattern synthesis which enables high-quality pattern projection using binary digital micromirror device patterns and multiplexing tens to hundreds of views. We utilize this approach to multiplex ∼150 ODT views in as few as 8 images and study how reconstruction quality changes with multiplexing. We demonstrate our approach on a variety of samples, including cells and diffusing colloidal particles.

Quantitative phase imaging (QPI) offers label-free access to refractive index information of biological samples, which can achieve nanometer-level optical-path-length sensitivity with cellular/sub-cellular biophysical and histological details. Recently we introduced quantitative oblique back-illumination microscopy (qOBM) which works in epi-mode and uses multiply scattered photons within thick samples to yield quantitative phase in thick scattering tissues, thus overcoming QPI’s long-standing limitation to thin transparent samples. qOBM provides real-time quantitative phase in 3D, and can be configured in a compact form factor. Here we describe a handheld qOBM probe, suitable for in-vivo diagnostic applications such as brain tumor assessment, dermatology, and more.

Tardigrades are microscopic animals known for their endurance at extreme temperatures and pressures. Tardigrade intrinsically disordered proteins (TDPs) are believed to contribute to such ability through stabilization of the membrane and cytosolic structures, increasing resistance to hyperosmotic stress, dehydration, and freezing. Mitochondria abundant heat soluble (MAHS) and cytosolic abundant heat soluble (CAHS) proteins are two variants of TDPs that localize to mitochondria and cytosol, respectively. These proteins retain their protective function when expressed in other species including bacteria, yeast, and mammalian cells. Owing to these features, the expression of tardigrade genes is believed to be a viable strategy for increasing in stress tolerance during cryopreservation. Despite the putative role of TDPs in stabilization of membrane, the mechanisms by which transgenic expression affects the membrane mechanical characteristics are unclear. Using quantitative phase imaging (QPI) in combination with optical tweezers, we present the mechanical behavior of the plasma membrane of malignant gliomas (U87 MG), and the transgenic variants of these cells expressing MAHS and CAHS as test cells. We found that the glioblastoma cells expressing MAHS and CAHS proteins portrayed distinctive force profiles and had lower tether diameter compared to non-transduced U87 cells, suggesting an alteration in mechanical behavior of the cell membrane.

The ubiquitous nature of microplastics in marine environments poses a significant threat to Atlantic salmon aquaculture, and fish in general. Mucosal surfaces are continuously exposed to microparticles – such as the skin epithelial layer with highly migrating keratocyte cells. This study applied the capabilities of Linnik-based Quantitative Phase Microscopy (QPM) equipped with a pseudo-thermal light source (PTLS) to examine the interactions between polystyrene microplastics (MPs) and Atlantic salmon keratocytes. The PTLS enables the QPM system to achieve high spatial phase sensitivity, allowing for the observation of precise morphological changes within the cell and migration in real time. Our study shows that cells that were exposed to polystyrene MPs exhibited dynamic fluctuations of the lamellipodia and provide evidence for early-stage phase membrane invaginations around the beads indicative of phagocytic activity. Implementation of QPM based on PTLS is a high-speed, non-invasive, label-free approach that provides vital insights into the morphological dynamics of MP exposure. This research not only contributes to the understanding of cellular morphological responses to microplastics in Atlantic salmon but also highlights the utility of advanced QPM imaging techniques from an environmental toxicology perspective.

Holographic tomography (HT) is one of the promising noninvasive quantitative optical phase imaging method, used to obtain the 3D refractive index (RI) distribution of biological samples in their native culture medium. Here, we report changes in the RI after KCl treatment on primary neurons using HT system.

We evaluated the application of quantitative phase imaging (QPI) with digital holographic microscopy (DHM) for the assessment of histopathological inflammation in patients with Ulcerative colitis (UC). Endoscopically obtained colonic and rectal mucosal biopsy samples from 21 patients with UC were analyzed by capturing DHM QPI images from which subsequently the subepithelial refractive index (RI) was determined. The retrieved RI data were correlated with established histological scoring systems including the Nancy index (NI) as well as with endoscopic and clinical findings. In conclusion, our data demonstrate DHM as a promising tool for quantitative assessment of mucosal inflammation in patients with UC.

We introduce GedankenNet, a self-supervised learning model for hologram reconstruction. During its training, GedankenNet leveraged a physics-consistency loss informed by the physical forward model of the imaging process, and simulated holograms generated from artificial random images with no correspondence to real-world samples. After this experimental-data-free training based on “Gedanken Experiments”, GedankenNet successfully generalized to experimental holograms on its first exposure to real-world experimental data, reconstructing complex fields of various samples. This self-supervised learning framework based on a physics-consistency loss and Gedanken experiments represents a significant step toward developing generalizable, robust and physics-driven AI models in computational microscopy and imaging.

The two-point correlation matrix comprises of correlation among the same or different transverse polarization field components at a pair of points. Here, we present a method to determine argument (phase) of the elements of the two-point correlation matrix of the polarized light from the correlation of the Stokes fluctuations. We use only two Stokes parameters S0 and S1 and their two-point correlations to measure all four elements of the two-point correlation matrix. Application of this technique is demonstrated in phase imaging from spatially fluctuating vector random field and in characterization of the partially coherent vector beam.

Quantitative oblique back-illumination microscopy (qOBM) is a label-free imaging technique that enables tomographic phase imaging of thick scattering samples with epi-illumination. Here, we propose the use of two forms of functional imaging with qOBM to study tissue and cell cultures. In doing so, we obtain the spatiotemporal and quantitative functional information associated with the phase values extrapolated from qOBM imaging. We have applied this process to study the efficacy of individual immune T cells to kill glioblastoma spheroid cultures in 3D spheroids. Data show that we can effectively distinguish between cell phenotypes and characterize the dynamic motion of these cells in 3D cultures. This work offers a distinct advantage in tracking 3D cellular dynamics in thick tissue as many function imaging modalities are limited to 2D samples. Further, this technology can be expanded to analyze a wide variety of cellular and subcellular dynamics non-invasively in thick tissue.

This paper introduces a simple arrangement for quantitative phase microscopy (QPM). We implement a compact and low-cost self-referencing setup for digital holographic microscopy (DHM). A glass plate (GP) is used to implement lateral shearing interferometry, and a glass microsphere (MS) takes on the responsibility of an objective lens. The usefulness and capability of the proposed system are validated by using it to resolve a standard grating structure, followed by validation with the results obtained from atomic force microscopy (AFM). We applied the setup to perform 3D visualizations of human red blood cells, demonstrating the technique’s potential for high-contrast label-free QPM of biological samples and its utility in cell morphology, identification, and classification.

In many quantitative phase imaging techniques, phase reconstruction is achieved by integrating information from two-dimensional gradient field. Although using both derivatives gives high-quality results, the acquisition time must be evenly distributed between each derivative. To minimize this time, we use a method that integrates from a single derivative. The challenge when integrating with only one derivative is the lack of information about the derivative in the orthogonal direction. To address this, a regularization parameter was introduced. By dealing with biological samples, we can have prior knowledge that ensures the absence of singularities in the perpendicular direction, justifying the introduction of this parameter. Our objective is to find a solution that minimizes the integration along the direction of the obtained derivative while simultaneously minimizing the norm of the derivative in the orthogonal direction using the introduced parameter. This allows us to perform integration without knowing one of the derivatives. Our method reduces processing time by utilizing Fourier properties, which are computationally efficient. We conclude that both the acquisition and processing time are reduced by not acquiring the derivative in one direction and utilizing Fourier properties for integration. We present experimental results showing the viability and potential of our proposal.

Quantitative phase microscopy (QPM), which quantifies the complex amplitude of forward-scattered (FS) light induced by specimens, enables the visualization of the macroscopic refractive index distribution in transparent samples and has been used for various applications such as dry mass analysis and cell cycle estimation. Conversely, interferometric scattering microscopy (iSCAT), which captures backward-scattered (BS) light, offers higher sensitivity compared to QPM and can effectively detect nanoparticles such as individual proteins and viruses, with the drawback of being unable to provide quantitative information on macrostructure. These microscopy techniques provide complementary information and have undergone independent advancements. In this study, we present bidirectional quantitative scattering microscopy (bidirectional QSM) for wide dynamic range imaging by simultaneously performing FS and BS measurements with a single image sensor using a digital holographic technique. This approach enables quantitative measurement of macrostructures as well as high sensitivity to nanoparticles. Moreover, digital holography facilitates the acquisition of complex amplitude FS and BS images, which allows simultaneous computational z-axis focusing, enabling subsequent quantitative correlation analysis between them. To provide a practical demonstration, time-lapse imaging of a cell is performed to characterize temporal changes in the state of cellular vital activity.

Quantitative Phase Imaging (QPI) holds immense promise as a powerful label-free and non-invasive clinical diagnostic tool, leveraging its exceptional sensitivity to phase shifts to capture high-quality and unique morphological data. However, as the adoption of deep learning algorithms becomes increasingly enticing for medical image analysis, clinicians’ apprehensions towards their black-box nature is a deterrent for the adoption of novel methods that rely on them. This study advocates for the integration of explainable AI techniques with QPI-based diagnostics to effectively interpret deep learning models' predictions, enabling them in aiding clinician decisions. Using radiation resistance in head and neck cancer as a model system, we investigate cells that have survived exposure to varying levels of radiation. We aim to identify subtle phenotypic differences induced by DNA damage, which might not be readily apparent without the application of sophisticated deep learning analysis. This investigation has the potential to provide valuable insights into the cellular responses to radiation and unravel intricate patterns that traditional analysis methods might overlook, possibly leading to actionable biomarkers. In addition, we compare the results of classical rule based interpretable methods with modern feature importance based explainability to answer - is the trade-off between interpretability and accuracy actually worth it? By providing transparent insights into the decision making process, explainable deep learning empowers clinicians to validate, interpret, and refine diagnostic outcomes, bridging the gap between cutting-edge technology and clinical practice.

Phase imaging and fluorescence microscopy provide valuable complementary information, and individually form the basis for a significant portion of the routing biological and biomedical optical imaging performed today. While multimodal phase and fluorescence microscopy has been explored for thin transparent samples to obtain structural information based on the refractive index distribution (with phase contrast) and molecular content (with fluorescence), combining these complementary technologies to study thick samples has been challenging and remains largely unexplored. This work presents the results of a study that combines quantitative phase imaging (QPI) and refractive index (RI) tomography in thick samples—using quantitative oblique back illumination—and bright field fluorescence deconvolution microscopy. The two technologies use a simple bright field microscope configuration with epi-illumination and through-focus z-stack acquisition, along with a deconvolution algorithm, to achieve 3D imaging. Phase and RI information is acquired nearly simultaneously with the fluorescence information with inherent co-registration of the two modalities. In this work, we will present the theoretical underpinning of this multimodal approach, describe the simple multimodal system, and show imaging results of thick tissues, such as labeled mice brains. This multimodal imaging approach could help biologists and clinicians gain a more comprehensive understanding of the tissue’s morphology and molecular composition, and can be widely applied across a number of biological and biomedical disciplines, including neuroscience, pathology, and oncology.

Digital holographic microscopy (DHM) has been demonstrated as a label-free minimally-invasive quantitative phase imaging (QPI) tool to assess the cytotoxic potential of nanoparticles in vitro. Due to low laser light intensities DHM minimizes interactions with the sample. The analyzed cell cultures thus remain in a native state, making them available for further downstream analysis. In a study on mouse macrophages (RAW 264.7) we explored if cell populations can be analyzed with common biochemical assays after the DHM-based QPI observation. Therefore, the mean effective concentration (EC₅₀) of poly(alkyl cyanoacrylate) nanocarriers was firstly determined based on the DHM accessible dry mass increment after 24 h. The results were then compared to corresponding data from two subsequently performed colorimetric cell viability and cytotoxicity assays. EC₅₀ values from all assays are found in good agreement and demonstrate the potential of QPI to achieve an increased data quality in in vitro cytotoxicity experiments.

Functional precision medicine aims to identify effective treatments for patients without targetable mutations. Current research in oncology screens patient-derived models of cancer using endpoint assays. However, these assays fail to capture dynamic responses and tumor heterogeneity. We developed multiparametric quantitative phase imaging (mQPI), a labelfree technique, to screen single cells in real-time. Our work shows mQPI correlates with endpoint assays in measuring drug response in cells from patient derived xenograft organoids (PDxOs), while also capturing time of response and singlecell heterogeneity. Additionally, we demonstrate that mQPI can differentiate organoids that come from the same patient, but which originated from different sites.

Quantitative phase imaging techniques (QPI) enable to observe transparent samples with high contrast and with quantitative information about their optical thickness. Among the vast family of QPI methods, two of them: (1) transport of intensity equation (TIE) and (2) digital in-line holographic microscopy (DIHM), rely on retrieving phase from several images collected with different defocus. In this work, we preliminarily investigate, mainly numerically under simulated conditions, the differences between those two methods, showing that TIE is more suitable for imaging lower-frequency objects with small defocus distance difference between collected images (around several micrometers). On the other hand, DIHM performs better for higher frequency objects and images collected with larger defocus distance difference (hundreds of micrometers). Moreover, our results show that DIHM achieves better results, when all collected images are relatively far from focal plane (in the millimeter range rather than in micrometer range), while for TIE this parameter does not have a significant influence onto the retrieved phase.

This study introduces a methodology for quantitative assessment of phase measurement sensitivity in lensless digital holographic microscopy (LDHM) setups, incorporating an immersion medium between the object and the detector. Utilizing two setup configurations, we systematically investigated the influence of immersion conditions on phase accuracy, numerical reconstruction, and twin-image artefacts. Employing the Angular Spectrum and iterative Gerchberg-Saxton methods, we reconstructed phase maps for varying immersion thicknesses. Results demonstrate that immersion medium has minimal influence on phase sensitivity but significantly reduces twin-image artifacts when in direct contact with the object, providing valuable insights for developing LDHM biological applications.

Lensless Digital Holographic Microscopy (LDHM) presents notable advantages, offering a wide field of view (FOV) for imaging with reasonable resolution, achieved through a relatively straightforward and cost-effective setup - typically comprising only a point source of light, a sample, and a camera. These properties, especially the wide FOV, make LDHM a promising tool for the population-wise characterization of biological cell cultures with single cell precision. Cell cultures grow in a controlled environment, and the slightest change in environmental conditions can have a significant impact. The same principles apply to imaging. Any alteration in the imaging process can disrupt natural growth and potentially lead to false conclusions during comparison to the control culture. A crucial challenge is to maintain the same environmental conditions. To address this, we propose a novel setup for simultaneous imaging on three parallel in-line LDHM systems, with cameras mounted on one rail (movable to realize multi-height hologram recording for iterative reconstruction), all sample holders mounted on the second rail, and all sources of light mounted on the third rail. Based on the collected holograms and their efficient reconstruction, it is possible to calculate migration parameters such as the average speed of a single cell or a predefined group of cells (e.g., big cells or slow cells) and statistics regarding cell number, size and speed over time.

Quantitative phase measurements in a Transport of intensity equation(TIE) based method requires capturing images at multiple defocussed positions. Using these intensity measurements along with the phase obtained we demonstrate an optimization algorithm that improves the quantitative phase estimation recovering the fine details that may be lost due to diffraction effects, aberrations and limitations of the TIE based method. We implement a cost minimization scheme to minimize the difference between measured and theoretically expected amplitude to improve the estimate of the required object field. Application of the method shows an improved accuracy in phase estimation of simulated and real objects.

This research introduces an innovative quantitative phase microscopy system employing a phase-contrast configuration. Azobenzene liquid crystal material serves as the phase-contrast modulator, and a polarization-sensing camera acts as the detector, capturing four-shifted images in a single shot. The quantitative phase information is then retrieved through a four-step phase-shifting algorithm. Our study establishes a correlation between the four detected polarization states and the Pancharatnam-Berry geometric phase characteristics of the liquid crystal material. This research holds significance as it advances our comprehension of single-shot QPM utilizing geometric phase and holds the potential to revolutionize real-time monitoring and 3D visualization across diverse biological scenarios.

Gender classification has found applications in various fields, including criminology, biometrics, and surveillance. Historically, different methods for gender identification have been employed, such as analyzing hand shape, gait, iris, and facial features. Fingerprints, being unique to each individual, are formed based on the control of multiple genes on chromosomes. After the 24th embryonic week, a person's fingerprint pattern remains unchanged throughout their life. Numerous studies have explored the use of fingerprints for various purposes, such as investigating mental characteristics, characteristics of hereditary diseases, and cancer screening. This paper focuses on studying fingerprints for the identification and classification of human gender through fingerprint analysis using in-line digital holography. The deep learning model constructed for this study includes two convolutional layers, pooling layers, and dense layers. It was trained on a biometric fingerprint database containing 6,000 images, achieving an impressive 99% accuracy. The model was then utilized to classify human gender based on fingerprint analysis, and its accuracy was tested using fingerprint images obtained through Inline Digital Holography (IDH) technique, achieving an 83% accuracy. The performance of the proposed system demonstrates that fingerprints contain vital features for effectively discriminating a person's gender.

Differential interference contrast (DIC) microscopy plays an important role in biological sample imaging, with the merit of high contrast, low phototoxicity and no fluorescent label required. Commercial DIC microscopy using Nomarski or Wollaston prism is based on the interference of two polarized waves with the 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, 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 and traditional microscopes, and showcases the promising and synergetic advancements in edge detection, particle motion tracking, and label-free cellular imaging.

Digital holography microscopy (DHM) has emerged as a powerful digital holographic imaging technique for dynamic three-dimensional phase reconstruction of microscopic samples. Recently, a Fresnel biprism has been introduced into the conventional DHM arrangement, making the configuration common path, off-axis and eliminating the requirement for different optical components, such as, beam-splitter, mirrors, etc. The recorded hologram in a DHM is mostly contaminated with speckle noise, which makes it difficult to interpret the phase information correctly. In the present work, we investigate the phase reconstruction accuracy in a Fresnel biprism based DHM, utilizing different Fourier terms, in the presence of low and high coherent sources. Different Fourier terms has been realised by modifying the recorded hologram in order to minimize the contribution of speckle noise in the reconstructed phase. Proof-of-concept simulation and experimental results are included for blood sample to demonstrate the accuracy in phase reconstruction in a Fresnel biprism based DHM.