Quantitative phase imaging and complex field reconstruction by pupil modulation differential phase contrast.

Optical diffraction tomography (ODT) is a promising label-free imaging method capable of quantitatively measuring the three-dimensional (3D) refractive index distribution of transparent samples. In recent years, partially coherent ODT (PC-ODT) has attracted increasing attention due to its system simplicity and absence of laser speckle noise. Quantitative phase imaging (QPI) technologies represented by Fourier ptychographic microscopy (FPM), differential phase contrast (DPC) imaging and intensity diffraction tomography (IDT) need to collect several or hundreds of intensity images, which usually introduce motion artifacts when shooting fast-moving targets, leading to a decrease in image quality. Hence, a quantitative real-time phase microscopy (qRPM) for extended depth of field (DOF) imaging based on 3D single-shot differential phase contrast (ssDPC) imaging method is proposed in this research study. qRPM incorporates a microlens array (MLA) to simultaneously collect spatial information and angular information. In subsequent optical information processing, a deconvolution method is used to obtain intensity stacks under different illumination angles in a raw light field image. Importing the obtained intensity stack into the 3D DPC imaging model is able to finally obtain the 3D refractive index distribution. The captured four-dimensional light field information enables the reconstruction of 3D information in a single snapshot and extending the DOF of qRPM. The imaging capability of the proposed qRPM system is experimental verified on different samples, achieve single-exposure 3D label-free imaging with an extended DOF for 160 µm which is nearly 30 times higher than the traditional microscope system.

Quantitative differential phase-contrast (DPC) imaging is one of the commonly used methods for phase retrieval. However, quantitative DPC imaging requires several pairwise intensity measurements, which makes it difficult to monitor living cells in real-time. In this study, we present a single-shot quantitative DPC imaging method based on the combination of deep learning (DL) and color-encoded illumination. Our goal is to train a model that can generate an isotropic quantitative phase image (i.e., target) directly from a single-shot intensity measurement (i.e., input). The target phase image was reconstructed using a linear-gradient pupil with two-axis measurements, and the model input was the measured color intensities obtained from a radially asymmetric color-encoded illumination pattern. The DL-based model was trained, validated, and tested using thirteen different cell lines. The total number of training, validation, and testing images was 264 (10 cells), 10 (1 cell), and 40 (2 cells), respectively. Our results show that the DL-based phase images are visually similar to the ground-truth phase images and have a high structural similarity index (>0.98). Moreover, the phase difference between the ground-truth and DL-based phase images was smaller than 13%. Our study shows the feasibility of using DL to generate quantitative phase imaging from a single-shot intensity measurement.

Dielectric metasurfaces have recently attracted much attention due to their ability to efficiently control light propagation, that is, its amplitude, phase and polarization, on micro- and macro- levels. Such metasurfaces also naturally allow for integration in compact optical setups due to their small sizes. An important issue of energy losses is also addressed by employing all-dielectric platform. Advancements in nanofabrication have enabled realization of metasurface-based high-resolution wavefront engineering devices, which have been employed in different imaging applications, for example, as metalenses, polarization filters, metaholograms, etc. Quantitative phase imaging is a powerful tool for the optical inspection of transparent samples in connection with biological and technical applications. By measuring thickness and/or refractive index profiles, phase imaging facilitates, for example, the observation of dynamic events in unstained cells. As such, it has become indispensable in biological imaging, wavefront correction and metrology. However, conventional cameras and photodetectors are inherently not sensitive to the phase of an incident lightwave. As a consequence, direct phase detection is challenging. Only by multiple intensity measurements or application of specialized interferometric schemes, the phase profile of an object can be in principle reconstructed. In this paper, we report on the ability of metasurfaces to contribute to quantitative phase imaging by independent control of the phase profiles in two orthogonal polarization states of an incident beam.

Fourier Ptychographic Microscopy (FPM) and Differential Phase Contrast (DPC) are quantitative phase imaging (QPI) methods that recover the complex transmittance function of a sample through coded illumination measurements and phase retrieval optimization. The successes of these methods rely upon acquiring several or possibly hundreds of illumination-encoded measurements. The multi-shot nature of such methods limits their temporal resolution. Similar to motion-induced blur during a long photographic exposure, motion occurring during these acquisitions causes spatial distortion and errors in the reconstructed phase, which inhibits these methods' ability to image fast moving live samples. Here we present a novel approach to correct for motion during QPI capture that relies on motion navigation to register measurements together prior to phase retrieval. The different illumination patterns required for QPI cause the measurements to have a different contrasts. This makes it difficult to use standard registration approaches to estimate complex sample motion directly from the measurements. Instead, we use a color-multiplexed navigator signal (red) that is comprised of a constant illumination pattern and leverage a color camera to separate it from the primary QPI information (green). The reliable motion estimate allows measurements to be shared across time points through image registration. This enables a full set of measurements for a phase retrieval problem to be solved at each time point. We demonstrate proof-of-concept experimental results in which blurring due to live sample motion (swimming Zebra fish, cell motion, and organelle movement) is reduced.

A well-known speckle which comes from the coherent property of laser source has limited the laser imaging application. Quantitative Phase Imaging (QPI) also suffers from this speckle noise when illuminate with coherent source. A rotational diffuser is a considerable method to minimize the speckle by averaging the speckle contrast in time. Here, we employ the dual optical diffuser-static and moving diffusers — to suppress speckle noise in QPI. Continuous-wave laser is used to illuminate polystyrene micro-bead as a sample. Due to the averaging independent speckle pattern, speckle noise in phase image is reduced by maintaining the quality of fringe. The ability of moving diffuser in speckle noise suppression is presented in Fourier domain via Fast Fourier Transform (FFT) technique and topographic phase map. This work proposes a valuable technique for efficient suppression of the coherent speckle in QPI.

Quantitative differential phase contrast (qDPC) microscopy enables high‐resolution, label‐free imaging of weakly absorbing samples by combining asymmetrical illumination with phase transfer function (PTF) deconvolution. However, conventional methods are limited by the ill‐posed nature of deconvolution and the band‐limited characteristics of the PTF, leading to poor robustness against noise and background fluctuations, particularly in thick or complex samples. To overcome these challenges, we propose a pupil‐driven differential phase contrast (PD‐DPC) framework that integrates system PTFs into both the data fidelity and regularization terms of the reconstruction model. The proposed model incorporates an edge‐sparsity‐promoting regularization to preserve structural detail and suppress noise, along with a Retinex‐inspired fidelity formulation to mitigate background fluctuations. The resulting non‐convex optimization problem is solved via an efficient Split Bregman algorithm with iterative reweighted soft‐thresholding. Simulations and experiments demonstrate that PD‐DPC outperforms L2‐DPC, Iso‐DPC, TV‐DPC, and Retinex‐DPC in terms of background suppression, phase fidelity, and edge preservation. The framework is compatible with diverse DPC modalities and enables automatic cell contour segmentation as well as high‐resolution imaging of absorbing tissues beyond the weak‐object approximation. By combining physics‐informed priors with a data‐adaptive reconstruction strategy, PD‐DPC offers a robust, broadly applicable solution that substantially enhances the accuracy and applicability of qDPC for biomedical imaging. The MATLAB code is available on GitHub .

Quantitative phase measurements at multiple wavelengths has created an opportunity for exploring new avenues in phase microscopy such as enhancing imaging-depth (1), measuring hemoglobin concentrations in erythrocytes (2), and more recently in tomographic mapping of the refractive index of live cells (3). To this end, quantitative phase imaging has been demonstrated both at few selected spectral points as well as with high spectral resolution (4,5). However, most of these developed techniques compromise imaging speed, field of view, or the spectral resolution to perform interferometric measurements at multiple colors. In the specific application of quantitative phase in studying blood diseases and red blood cells, current techniques lack the required sensitivity to quantify biological properties of interest at individual cell level. Recently, we have set out to develop a stable quantitative interferometric microscope allowing for measurements of such properties for red cells without compromising field of view or speed of the measurements. The feasibility of the approach will be initially demonstrated in measuring dispersion curves of known solutions, followed by measuring biological properties of red cells in sickle cell anemia.

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.

Quantitative phase imaging (QPI) has advanced by accurately quantifying phase shifts caused by weakly absorbing biological and artificial structures. Despite extensive research, the diffraction limits of QPI have not been established and examined. Hence, it remains unclear whether diffraction-affected QPI provides reliable quantification or merely visualizes phase objects, similar to phase contrast methods. Here, we develop a general diffraction phase imaging theory and show that it is intrinsically connected with Rayleigh’s resolution theory. Our approach reveals the entanglement of phases under restoration, imposing diffraction bounds on spatial phase resolution and, unexpectedly, on phase accuracy. We prove that the phase accuracy depends on the size, shape, and absorption of objects forming the sample and significantly declines if the object size approaches the Rayleigh limit (a relative phase error of −16% for an Airy disk-sized object with low phase shift). We show that the phase accuracy limits can be enhanced at the cost of deteriorated phase resolution by attenuating the sample background light. The QPI diffraction limits are thoroughly examined in experiments with certified phase targets and biological cells. The study’s relevance is underscored by results showing that the phase accuracy of some structures is lost (a relative phase error of −40%) even though they are spatially resolved (a phase visibility of 0.5). A reliable procedure is used to estimate phase errors in given experimental conditions, opening the way to mitigate errors’ impact through data post-processing. Finally, the phase accuracy enhancement in super-resolution QPI is discovered, which has not been previously reported.

Quantitative differential phase contrast (DPC) microscopy has been developed to retrieval the phase of object leveraged from weak object assumption. In perspective of transfer function of DPC, deviating from that with coherent illumination, the DPC reveals non-isotropic transfer function under partial coherent illumination. Therefore, multi-axis measurements would be necessary to formulate the isotropic response for quantitative DPC phase imaging. In this paper, the gradient amplitude modulation is used to generate the isotropic DPC transfer function with only two-axis measurements. We show our modeling and simulation results.

Quantitative phase microscopy (QPM) is a label-free imaging technique often employed for long-term, high-contrast imaging of live bio-samples. Yet, QPM is not specific to a certain subcellular organelle. As a remedy, fluorescence microscopy can visualize specific subcellular organelles once being labeled with fluorescent markers. In this paper, a high-resolution phase/fluorescence dual-modality microscopic imaging method based on structured light illumination is proposed. In a dual-modality microscopic system, periodic stripes are generated by a digital micromirror array (DMD), and are used as the common illumination for both modalities. For QPM imaging, the holograms of the sample under structured light illuminations from different directions and phase shifts are recorded, from which a quantitative phase image with resolution enhancement can be reconstructed via a synthetic aperture procedure. Furthermore, a numerical approach is proposed to compensate for the environmental disturbances that often challenge aperture synthesis of phase imaging. This method determines each time the phase distortions caused by environmental disturbances through using the spectrum of the 0th order of the structured light illumination, and the phase distortions are removed from the phase distributions of the waves along the 0th and the ±1st diffraction orders. Resolution enhancement of QPM imaging is realized by synthesizing the spectra of all the waves along different diffraction orders of the structured light illuminations of different orientations. With phase images, three-dimensional shapes, inner structures, or refractive index distributions of transparent and translucent samples can be obtained. For fluorescence imaging, intensity images (morie patterns) of the sample under different structured light illuminations are recorded. The spectra along different diffraction orders are separated by using a phase shifting reconstruction algorithm, and are shifted to their original positions, forming a synthesized spectrum that is much broader than the spectra of raw intensity images (NA-limited spectra). An inverse Fourier transform on the synthesized spectrum yields a super-resolution fluorescence image of the sample. With the reconstructed fluorescence images, specific subcellular organelles labeled with fluorescent markers can be visualized. The combination of quantitative phase microscopy and fluorescence microscopy can obtain multidimensional information about the sample. In this dual-mode imaging system, the spatial resolution of quantitative phase imaging and fluorescence imaging are 840 nm and 440 nm, respectively. The proposed dual-mode microscopy imaging technique has been demonstrated for imaging fluorescent beads, fly wings, spring/rice leaves, mouse tail transection, and fluorescence-stained SiHa cells. We envisage that this method can be further applied to many fields, such as biomedicine, industry, and chemistry.

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.

The combination of multiple imaging modalities in a single microscopy system can enable new insights into biological processes. In this work, we describe the construction and rigorous characterization of a custom microscope with multimodal imaging in a single, cost-effective system. Our design utilizes advances in LED technology, robotics, and open-source software, along with existing optical components and precision optomechanical parts to offer a modular and versatile design. This microscope is operated using software written in Arduino and Python and has the ability to run multi-day automated imaging experiments when placed inside of a cell culture incubator. Additionally, we provide and demonstrate methods to validate images taken in brightfield and darkfield, along with validation and optimization for differential phase contrast (DPC) quantitative phase imaging.

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

Wedge prism assisted quantitative phase imaging on standard microscopes