Full optical characterization of single nanoparticles using quantitative phase imaging

Quantitative phase imaging (QPI) has emerged as a powerful tool in label-free bioimaging, in situ microstructure characterization for advanced manufacturing, and high-speed imaging of material property changes. Among various QPI methods, quadri-wave lateral shearing interferometry (QWLSI) stands out for its unique advantages in compactness, robustness, and high temporal resolution, making it an ideal choice for a wide range of applications. The compact design of QWLSI allows for easy integration with existing microscopy systems, while its robustness is manifested in the ability to maintain precise interferometric sensitivity even in high-vibration environments. Moreover, QWLSI also enables single-shot measurements that facilitate the capture of fast dynamic processes. This paper provides an in-depth exploration of the technical aspects of QWLSI, focusing on the evolution of its optical system and the primary algorithms used in wavefront reconstruction. The review also showcases significant applications of QWLSI, with a particular emphasis on its contributions to biomedical imaging. By discussing the advantages, limitations, and potential future developments of QWLSI, this paper aims to provide a comprehensive overview of this powerful QPI technique and its impact on various research fields.

Quadriwave lateral shearing interferometry (QLSI) is a powerful quantitative phase imaging technique, offering compactness, robustness, high resolution, and single-shot measurement. However, since QLSI phase retrieval relies primarily on phase gradient integration, it may struggle with speckle beams containing phase singularities, where phase discontinuities lead to non-conservative gradients and reduce integration accuracy. Here, we propose a convolutional neural network (CNN)-assisted QLSI sensing method for speckle beam reconstruction. The CNN is trained to directly retrieve the complex amplitude information of speckle beams from their QLSI interferograms. Experimental results demonstrate that the proposed method can accurately reconstruct both amplitude and phase profiles of speckle beams with various complexities, achieving a Pearson correlation coefficient exceeding 0.9 compared to the ground truth. This method is expected to enhance the sensing capability of traditional QLSI wavefront sensors and enable broader applications, such as free-space laser communication and advanced optical imaging in strong turbulence scenarios.

It is well known that the quantitative phase information which is vital in the biomedical study is hard to be directly obtained with bright-field microscopy under incoherent illumination. In addition, it is impossible to maintain the living sample in focus over long-term observation. Therefore, both the autofocusing and quantitative phase imaging techniques have to be solved in microscopy simultaneously. Here, we propose a lightweight deep learning-based framework, which is constructed by residual structure and is constrained by a novel loss function model, to realize both autofocusing and quantitative phase imaging. It outputs the corresponding in-focus amplitude and phase information at high speed (10fps) from a single-shot out-of-focus bright-field image. The training data were captured with a designed system under a hybrid incoherent and coherent illumination system. The experimental results verify that the focused and quantitative phase images of non-biological samples and biological samples can be reconstructed by using the framework. It provides a versatile quantitative technique for continuous monitoring of living cells in long-term and label-free imaging by using a traditional incoherent illumination microscopy system.

A cellular-level study of the pathophysiology is crucial for understanding the mechanisms behind human diseases. Recent advances in quantitative phase imaging (QPI) techniques show promises for the cellular-level understanding of the pathophysiology of diseases. To provide important insight on how the QPI techniques potentially improve the study of cell pathophysiology, here we present the principles of QPI and highlight some of the recent applications of QPI ranging from cell homeostasis to infectious diseases and cancer.

Inflammatory bowel diseases (IBD) are inflammatory disorders of the gastrointestinal tract characterized by a chronic relapsing disease course. As uncontrolled intestinal inflammation can result in severe disease complications, recent treatment targets of IBD evolved toward seeking the absence of mucosal and histological inflammation. However, this approach requires adequate histological evaluation of IBD disease activity. The diagnostic challenge of histological examination of intestinal inflammation is documented by the multitude of proposed histological scoring systems. In this context, we review quantitative phase imaging (QPI) techniques such as digital holographic microscopy (DHM) for characterizing intestinal inflammation. DHM determines optical path-length delays in a stain-free manner, thereby providing the tissue refractive index as a biophysical marker that directly correlates to tissue density. Recently, DHM has been successfully applied in cell biology, cancer cell research and infectious-induced cellular alterations. We summarized the capabilities of DHM and related QPI techniques to assess the severity of intestinal inflammation in experimental colitis as well as in colonic samples from human IBD patients. Moreover, we illustrate major advantages of DHM facilitated multimodal evaluation of epithelial wound healing processes as assessed by physical parameters like cell volume, density, thickness and dry mass in vitro. Furthermore, potential limitations of DHM and future utilities of QPI are discussed. In conclusion, DHM represents a promising, easy-to-use quantitative tool to provide accurate and objective assessment of intestinal inflammation and may pave the way towards automated label-free digital pathology and related in vitro cell culture analysis in future.

Biological cells are composed primarily of water; and as such are challenging to image without staining since the induced intensity modulation of transmitted or reflected light is typically insufficient to permit acceptable contrast for optical imaging. This issue may be resolved with the aid of exogenous contrast agents, but this often has a deleterious effect on the cell and precludes in vivo imaging. A unique approach to this problem is afforded by the phase contrast microscope in which optical-path differences in transmitted light is exploited as a contrast mechanism for qualitative imaging. In recent years however, several quantitative phase imaging techniques have been developed which allow for diffraction limited endogenous-contrast imaging with excellent temporal resolution. We hereby present a laser scanning technique for quantitative phase imaging which achieves sub-diffraction limited resolution at the expense of temporal resolution. This instrument is based on a stabilized fiber interfometer which is incorporated into a near-field scanning optical microscope (NSOM) for tri-modal imaging. Our latest results will focus on modifications made to this system to facilitate imaging in a liquid environment. A simple approach for achieving stable shear-force feedback operation in a liquid will be presented. Acquired high resolution images of white blood cells revealed detailed sub-cellular features. Images of fibroblast cells in air and in a liquid environment confirm the efficacy of the feedback operation in a liquid. Moreover, we demonstrate cell refractometry capability without the need for ad hoc modifications. These results clearly highlight the unique potential of this instrument for the study of living cells.

We report the characterization of all the relevant biomechanical properties of individual red blood cells with sickle cell disease using non-invasive quantitative phase imaging and spectroscopy techniques with a previously-validated RBC membrane model.

We present a new interferometric and holographic approach which allows for multiple depth multiplexing in a single acquisition, using an off-axis low-coherence interferometric imaging system. This technique enables quantitative amplitude and phase imaging of multiple slices within a thicker sample, in one single image acquisition. The method is implemented using a compact interferometric module that connects to a regular digital camera, and is useful in a wide range of applications in which multiple z slices of a sample are required simultaneously. The simultaneous acquisition is carried out by using optical multiplexing of the interferograms on the camera, whereby each slice has a distinct off axis interference fringe direction in relation to the other. We demonstrate the proposed technique for quantitative optical thickness imaging of microscopic biological samples.

Hybrid Random Walk-Linear Discriminant Analysis Method for Unwrapping Quantitative Phase Images of Biological Samples

We present quantitative optical measurements of individual human red blood cells from both diabetes patients and healthy blood donors using 3-D quantitative phase imaging technique in a noninvasive manner.

Interaction between intracellular compartments is based on complex vesicular transport processes. Fluorescence based techniques now reach single molecule resolution in living cells. To avoid fluorophore photobleaching limitations, quantitative phase imaging techniques are conventionally used to produce long-term high contrast cell images. We used an improved wave front sensing set-up called QWLSI-HD, which resolution is high enough to reach nanometric resolution for vesicle localization. We also added specificity to quantitative phase imaging by training artificial intelligence algorithms to recognize intracellular vesicles. We compared performances between the algorithms and also between fixed and living samples.

Quantitative phase imaging (QPI) technique is used to determine various biophysical parameters, such as refractive index, cell thickness, morphology, etc. On the other hand, fluorescence microscopy is used to acquire information regarding molecular specificity of the biological cells and tissues. Conventionally, a fully coherent light source such as laser is used in QPI technique to obtain the interference fringes with ease; however, its high coherence is also responsible for the generation of speckle and spurious fringes, which results in degraded image quality and affects the phase measurement results too. In this paper, we report a multi-modal system that can be effectively utilized to acquire time varied diverse information about the biological specimen with high spatial phase sensitivity. Herein, a single unit comprising of a fluorescence microscope and the Linnik based interferometer specially equipped with a partially spatially coherent light source illumination was developed. The integrated system is capable to procure molecular specificity and phase information of biological specimen, in a single shot, utilizing a single-chip color CCD camera. Here, we performed experiments on MG63 osteosarcoma cells, and the composite interferometric-fluorescence images were obtained and then digitally decomposed into red and green colors; and, the phase maps were reconstructed using the Fourier fringe analysis method. Furthermore, the cultured cells were monitored over a time-span to observe and investigate the time dependent morphological changes along with the quantification of cellular adhesion and spreading. Hence, the proposed system can be utilized to quantify time dependent changes in the cell’s morphology and in cell adhesion which can be an indicator for the detection of various range of diseases such as arthritis, cancer, osteoporosis and atherosclerosis.

White light diffraction phase microscopy with slightly off-axis blind two-step phase-shifting

Existing quantitative phase imaging (QPI) techniques are faced with an inherent trade-off between phase imaging fidelity and temporal resolution. Here, we propose a general algorithmic framework for QPI reconstruction that enables frame-rate-limited holographic imaging. It takes an inverse problem approach by formulating phase retrieval as a nonsmooth nonconvex optimization problem. Efficient solvers for the problem are derived whose algorithmic behaviors have been studied from both theoretical and experimental perspectives. The proposed framework is applicable to various existing holographic imaging configurations, and makes it possible to incorporate advanced image priors for quality enhancement.

Achieving high-contrast, label-free imaging with minimal impact on live cell culture behavior remains a primary challenge in quantitative phase imaging (QPI). By enabling imaging under low illumination intensities (low photon budget, LPB), it is possible to minimize cell photostimulation, phototoxicity, and photodamage while supporting long-term and high-speed observations. However, LPB imaging introduces significant difficulties in QPI due to high levels of camera shot noise and quantification noise. Digital in-line holographic microscopy (DIHM) is a QPI technique known for its robustness against LPB data. However, simultaneous minimization of shot noise and inherent in DIHM twin image perturbation remains a critical challenge. In this study, we present the iterative Gabor averaging (IGA) algorithm, a novel approach that integrates iterative phase retrieval with frame averaging to effectively suppress both twin image disturbance and shot noise in multiframe DIHM. The IGA algorithm achieves this by leveraging an iterative process that reconstructs high-fidelity phase images while selectively averaging camera shot noise across frames. Our simulations demonstrate that IGA consistently outperforms conventional methods, achieving superior reconstruction accuracy, particularly under high-noise conditions. Experimental validations involving high-speed imaging of dynamic sperm cells and a static phase test target measurement under low illumination further confirmed IGA's efficacy. The algorithm also proved successful for optically thin samples, which often yield low signal-to-noise holograms even at high photon budgets. These advancements make IGA a powerful tool for photostimulation-free, high-speed imaging of dynamic biological samples and enhance the ability to image samples with extremely low optical thickness, potentially transforming biomedical and environmental applications in low-light settings.