Quantitative Differential Phase Contrast Research Articles

Plug-and-play DPC-based quantitative phase microscope.

Point-of-care testing (POCT) plays an increasingly important role in biomedical research and health care. Quantitative phase microscopes (QPMs) with good contrast, no invasion, no labeling, high speed and automation could be effectively applied for POCT. However, most QPMs are fixed on the optical platform with bulky size, lack of timeliness, which remained challenging in POCT solutions. In this paper, we proposed a plug-and-play QPM with multimode imaging based on the quantitative differential phase contrast (qDPC) method. The system employs a programmable LED array as the light source and uses the GPU to accelerate the calculation, which can realize multi-contrast imaging with six modes. Accurate phase measurement and real-time phase imaging are implemented by the proposed qDPC algorithms for quantitative phase targets and biomedical samples. A 3D electric control platform is designed for mechanical control of field of view and focusing without manual operations. The experimental results verify the robustness and high performance of the setup. Even a rookie could finish the POCT scheme for biomedical applications at the scene using the QPM with a compact size of 140 × 165 × 250 mm3.

Simple implementation of aperture modulation quantitative differential phase contrast imaging

As one of the quantitative phase imaging methods, aperture modulation quantitative differential phase contrast (amqDPC) imaging has isotropic lateral resolution, being widely used in many fields such as biological cell morphology detection. However, the devices required to implement it are poorly controlled and very expensive. In addition, due to the weak phase approximation, there is a large axial phase error, and the full spectrum center pass during aperture modulation will cause distortion. Therefore, a method that enables simple and low-cost implementation of amqDPC, high axial phase accuracy, and isotopic lateral resolution is reported. Through simulations and experimental verifications, axial accuracy is greatly improved in the phase range of [0, π], and an isotropic lateral resolution of 870 nm can be achieved. In addition, experiments on transparent glass circular step sample and mouse kidney tissue slice also prove the practicability of this method. According to this study, researchers can accurately and simply measure the axial height of a slightly thick sample, which is achieved by capturing two intensity images to reconstruct a quantitative phase.

Single-shot quantitative differential phase contrast imaging combined with programmable polarization multiplexing illumination.

We propose a single-shot quantitative differential phase contrast method with polarization multiplexing illumination. In the illumination module of our system, a programmable LED array is divided into four quadrants and covered with polarizing films of four different polarization angles. We use a polarization camera with polarizers before the pixels in the imaging module. By matching the polarization angle between the polarizing films over the custom LED array and the polarizers in the camera, two sets of asymmetric illumination acquisition images can be calculated from a single-shot acquisition image. Combined with the phase transfer function, we can calculate the quantitative phase of the sample. We present the design, implementation, and experimental image data demonstrating the ability of our method to obtain quantitative phase images of a phase resolution target, as well as Hela cells.

Single-shot quantitative phase contrast imaging based on deep learning.

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.

Self-supervised neural network for phase retrieval in QDPC microscopy.

Quantitative differential phase contrast (QDPC) microscope plays an important role in biomedical research since it can provide high-resolution images and quantitative phase information for thin transparent objects without staining. With weak phase assumption, the retrieval of phase information in QDPC can be treated as a linearly inverse problem which can be solved by Tikhonov regularization. However, the weak phase assumption is limited to thin objects, and tuning the regularization parameter manually is inconvenient. A self-supervised learning method based on deep image prior (DIP) is proposed to retrieve phase information from intensity measurements. The DIP model that takes intensity measurements as input is trained to output phase image. To achieve this goal, a physical layer that synthesizes the intensity measurements from the predicted phase is used. By minimizing the difference between the measured and predicted intensities, the trained DIP model is expected to reconstruct the phase image from its intensity measurements. To evaluate the performance of the proposed method, we conducted two phantom studies and reconstructed the micro-lens array and standard phase targets with different phase values. In the experimental results, the deviation of the reconstructed phase values obtained from the proposed method was less than 10% of the theoretical values. Our results show the feasibility of the proposed methods to predict quantitative phase with high accuracy, and no use of ground truth phase.

Quantitative differential phase contrast imaging in an LED array microscope: errata.

This errata corrects typos found in the derived transfer functions in [Opt. Express23, 11394 (2015)10.1364/OE.23.011394].

Single-shot color-coded LED microscopy for quantitative differential phase contrast imaging

Common quantitative differential phase contrast microscopy imaging usually uses multistep circular or annular illuminations and color multiplexed illuminations, bringing about low capture efficiency and poor phase reconstruction, respectively. We present a new single-shot quantitative differential phase contrast microscopy imaging method, which uses R/B-G annular LED multiplexed illumination to achieve better phase reconstruction by capturing 1 colored image. By deriving the phase transfer function of the illumination and simulation verification, the superiority of it is confirmed. Through phase reconstruction simulations for circular step and gradual samples, we verify that the R/B-G annular multiplexed illumination has better axial phase reconstruction accuracy and weaker lateral anisotropy than other color multiplexed illuminations. As a demonstration, quantitative phase imaging is performed on Quantitative Phase Target, validating the axial accuracy, lateral resolution, and lateral anisotropy of our method. Imaging and phase reconstruction were also performed on mouse kidney tissue slice and motional silica microspheres to visually express the utility and practicability of this method. Our research provides a better color multiplexed avenue for the real-time quantitative phase imaging in dispersion-free, weak-phase samples, especially living biological tissues.

Quantitative differential phase contrast phase reconstruction for sparse samples

Quantitative differential phase contrast (qDPC) microscopy can achieve phase imaging of unlabeled cell samples with high spatial resolution. However, qDPC imaging is easily affected by the noise generated in the experiments. In this manuscript, the L0-norm regularization was introduced into qDPC phase reconstruction for sparse samples (L0-qDPC), including the quantitative phase target and cell samples. After the detailed comparison of phase fidelity, imaging contrast, resolution, and convergence rate, L0-qDPC method can provide a stable qDPC phase imaging without parameter adjustment for sparse samples due to strong constraint and good robustness of L0-norm based on sparse prior, compared with the L2-norm and total variation regularization.

Retinex-qDPC: Automatic background-rectified quantitative differential phase contrast imaging

Background and objectiveThe quality of quantitative differential phase contrast reconstruction (qDPC) can be severely degenerated by the mismatch of the background of two oblique illuminated images, yielding problematic phase recovery results. These background mismatches may result from illumination patterns, inhomogeneous media distribution, or other defocusing layers. In previous reports, the background is manually calibrated which is time-consuming, and unstable, since new calibrations are needed if any modification to the optical system was made. It is also impossible to calibrate the background from the defocusing layers, or for high dynamic observation as the background changes over time. The background mismatch reduces the experimental robustness of qDPC and largely limits its applications. To tackle the mismatch of background and increases the experimental robustness, we propose the Retinex-qDPC. MethodsIn Retinex-qDPC, we replace the data fidelity term of the previous cost function for qDPC inverse problem, by the images’ edge features yielding L2-Retinex-qDPC and L1-Retinex-qDPC for high background-robustness qDPC reconstruction. The split Bregman method is used to solve the L1-Retinex DPC. We compare both Retinex-qDPC models against state-of-the-art DPC reconstruction algorithms including total-variation regularized qDPC, and isotropic-qDPC using both simulated and experimental data. ResultsRetinex qDPC can significantly improve the phase recovery quality by suppressing the impact of mismatch background. Within, the L1-Retinex-qDPC is better than L2-Retinex and other state-of-the-art qDPC algorithms. ConclusionsThe Retinex-qDPC increases the experimental robustness against background illumination without any modification of the optical system, which will benefit all qDPC applications.

Time-lapse imaging using dual-color coded quantitative differential phase contrast microscopy.

.Significance: Quantitative differential phase contrast (qDPC) microscopy enhances phase contrast by asymmetric illumination using partially coherent light and multiple intensity measurements. However, for live cell imaging, motion artifacts and image acquisition time are important issues. For live cell imaging, a large number of intensity measurements can limit the imaging quality and speed. The minimum number of intensity measurements in qDPC can greatly enhance performance for live imaging.Aim: To obtain high-contrast, isotropic qDPC images with two intensity measurements and perform time-lapse imaging of biological samples.Approach: Based on the color-coded design, a dual-color linear-gradient pupil is proposed to achieve isotropic phase contrast response with two intensity measurements. In our method, the purpose of designing a dual-color coded pupil is twofold: first, to obtain a linear amplitude gradient for asymmetric illumination, which is required to get a circular symmetry of transfer function, and second, to reduce the required number of frames for phase retrieval.Results: To demonstrate the imaging performance of our system, standard microlens arrays were used as samples. We performed time-lapse quantitative phase imaging of rat astrocytes under a low-oxygen environment. Detailed morphology and dynamic changes such as the apoptosis process and migration of cells were observed.Conclusions: It is shown that dual-color linear-gradient pupils in qDPC can outperform half-circle and vortex pupils, and isotropic phase transfer function can be achieved with only two-axis measurements. The reduced number of frames helps in achieving faster imaging speed as compared to the typical qDPC system. The imaging performance of our system is evaluated by time-lapse imaging of rat astrocytes. Different morphological changes in cells during their life cycle were observed in terms of quantitative phase change values.

Morphology analysis of unlabeled red blood cells based on quantitative differential phase contrast microscopy.

The current classical blood smear technique to observe the morphology of single red blood cells (RBCs) for classification is a laborious and error-prone process. To objectively evaluate the morphology of blood cells, we established a method of computational imaging based on a programmable light emitting diode array. By using quantitative differential phase contrast (qDPC), we characterized the morphology of unlabeled RBCs as well as blood smears. By focusing on comparing the difference of imaging between unlabeled RBCs and stained RBCs under multimode microscopic imaging technology, we demonstrated that qDPC could clearly differentiate discocytes and spherocytes in both unlabeled RBCs and blood smears. The phase map provided by quantitative phase imaging further enhanced the classification accuracy. According to statistical analysis from morphological indexes, the qDPC imaging has a significantly improvement in non-circularity, texture inhomogeneity and equivalent diameters of cells. Thus, this method has a significant superiority in the capability to analyze the morphology of RBCs and could be applied to clinical assays for determining morphological, functional, and structural deterioration of RBCs.

Low-coherence quantitative differential phase-contrast microscopy using Talbot interferometry.

This paper presents a simple, cost-efficient, and highly stable quantitative differential phase-contrast (PC) microscopy based on Talbot interferometry. The proposed system is composed of an optical microscope coupled with a pair of Ronchi amplitude gratings that utilizes a light-emitting diode as a low temporal coherence light source. The quantitative differential PC images of the microscopic transparent samples are reconstructed by analyzing the deformation of moiré patterns using a phase-shifting procedure. Low temporal coherence leads to eliminating speckle noise and undesirable interferences to obtain high-quality images. The spatial phase stability of the system is investigated and compared to two other common-path interferometers. Additionally, the performance of the method is verified by the experimental results of a standard resolution test target and phase biological samples.

Factors limiting quantitative phase retrieval in atomic-resolution differential phase contrast scanning transmission electron microscopy using a segmented detector

Quantitative differential phase contrast imaging of materials in atomic-resolution scanning transmission electron microscopy using segmented detectors is limited by various factors, including coherent and incoherent aberrations, detector positioning and uniformity, and scan-distortion. By comparing experimental case studies of monolayer and few-layer graphene with image simulations, we explore which parameters require the most precise characterisation for reliable and quantitative interpretation of the reconstructed phases. Coherent and incoherent lens aberrations are found to have the most significant impact. For images over a large field of view, the impact of noise and non-periodic boundary conditions are appreciable, but in this case study have less of an impact than artefacts introduced by beam deflections coupling to beam scanning (imperfect tilt-shift purity).

Patch-Based U-Net Model for Isotropic Quantitative Differential Phase Contrast Imaging.

Quantitative differential phase-contrast (qDPC) imaging is a label-free phase retrieval method for weak phase objects using asymmetric illumination. However, qDPC imaging with fewer intensity measurements leads to anisotropic phase distribution in reconstructed images. In order to obtain isotropic phase transfer function, multiple measurements are required; thus, it is a time-consuming process. Here, we propose the feasibility of using deep learning (DL) method for isotropic qDPC microscopy from the least number of measurements. We utilize a commonly used convolutional neural network namely U-net architecture, trained to generate 12-axis isotropic reconstructed cell images (i.e. output) from 1-axis anisotropic cell images (i.e. input). To further extend the number of images for training, the U-net model is trained with a patch-wise approach. In this work, seven different types of living cell images were used for training, validation, and testing datasets. The results obtained from testing datasets show that our proposed DL-based method generates 1-axis qDPC images of similar accuracy to 12-axis measurements. The quantitative phase value in the region of interest is recovered from 66% up to 97%, compared to ground-truth values, providing solid evidence for improved phase uniformity, as well as retrieved missing spatial frequencies in 1-axis reconstructed images. In addition, results from our model are compared with paired and unpaired CycleGANs. Higher PSNR and SSIM values show the advantage of using the U-net model for isotropic qDPC microscopy. The proposed DL-based method may help in performing high-resolution quantitative studies for cell biology.

Isotropic quantitative differential phase contrast microscopy using radially asymmetric color-encoded pupil

Differential phase contrast (DPC) microscopy provides isotropic phase images by applying asymmetric illumination patterns on the sample. The movement of specimens during series image acquisition may lead to motion blur artifacts, which are difficult to prevent. Here, we propose a new method based on pupil engineering and color multiplexing to obtain an isotropic phase transfer function and to reduce the required frames simultaneously. Radially asymmetric color pupils are implemented in a DPC microscope using a programmable thin-film transistor as a digital pupil, which gives flexibility and dynamic control for projecting illumination patterns on samples. With our approach, an isotropic quantitative phase map can be obtained using only pairwise color images for phase reconstruction. A radially asymmetric color pupil is synthesized by encoding the red, green, and blue colors. To recover accurate phase values, a color-leakage correction algorithm is applied to calibrate each color channel. Compared to a half-circle illumination pupil, our method can significantly enhance the image acquisition speed. The phase recovery accuracy is more than 97%. To show the imaging performance of our proposed method, quantitative phase imaging of living 3T3 mouse fibroblast cells is performed. Our quantitative phase measurement method may find important applications in biomedical research.

Transmission Structured Illumination Microscopy for Quantitative Phase and Scattering Imaging

In this paper, we demonstrate a digital micromirror device (DMD) based optical microscopic apparatus for quantitative differential phase contrast (qDIC) imaging, coherent structured illumination microscopy (SIM), and dual-modality (scattering/fluorescent) imaging. For both the qDIC imaging and the coherent SIM, two sets of fringe patterns with orthogonal orientations and five phase-shifts for each orientation, are generated by a DMD and projected on a sample. A CCD camera records the generated images in a defocusing manner for qDIC and an in-focus manner for coherent SIM. Both quantitative phase images and super-resolved scattering/fluorescence images can be reconstructed from the recorded intensity images. Moreover, fluorescent imaging modality is integrated, providing specific biochemical structures of the sample once using fluorescent labeling.

Multi-wavelength quantitative differential phase contrast imaging by radially asymmetric illumination.

A new approach for achieving isotropic differential phase contrast imaging by applying multi-wavelength asymmetric illumination is demonstrated. Multi-wavelength isotropic differential phase contrast scheme (MW-iDPC) can be implemented using an add-on module in any commercial inverted microscope. Isotropy of intensity transfer function is achieved using three axis measurements. The expression for MW-iDPC imaging is presented, and detailed mathematical analysis is performed for transfer function. By applying color leakage correction, image sensor responses can be calibrated. Asymmetric illumination masks are designed, and simulation studies for intensity of the transfer function are performed. We utilize the MW-iDPC system to reconstruct quantitative phase images of standard microspheres and live breast cancer cells. The optical thickness ofcells can be measured with high accuracy and image acquisition time is reduced significantly.

Optimal illumination scheme for isotropic quantitative differential phase contrast microscopy

Differential phase contrast microscopy (DPC) provides high-resolution quantitative phase distribution of thin transparent samples under multi-axis asymmetric illuminations. Typically, illumination in DPC microscopic systems is designed with two-axis half-circle amplitude patterns, which, however, result in a non-isotropic phase contrast transfer function (PTF). Efforts have been made to achieve isotropic DPC by replacing the conventional half-circle illumination aperture with radially asymmetric patterns with three-axis illumination or gradient amplitude patterns with two-axis illumination. Nevertheless, the underlying theoretical mechanism of isotropic PTF has not been explored, and thus, the optimal illumination scheme cannot be determined. Furthermore, the frequency responses of the PTFs under these engineered illuminations have not been fully optimized, leading to suboptimal phase contrast and signal-to-noise ratio for phase reconstruction. In this paper, we provide a rigorous theoretical analysis about the necessary and sufficient conditions for DPC to achieve isotropic PTF. In addition, we derive the optimal illumination scheme to maximize the frequency response for both low and high frequencies (from 0 to 2NAobj) and meanwhile achieve perfectly isotropic PTF with only two-axis intensity measurements. We present the derivation, implementation, simulation, and experimental results demonstrating the superiority of our method over existing illumination schemes in both the phase reconstruction accuracy and noise-robustness.

Quantitative differential phase contrast (DPC) microscopy with computational aberration correction.

Differential Phase Contrast (DPC) microscopy is a practical method for recovering quantitative phase from intensity images captured with different source patterns in an LED array microscope. Being a partially coherent imaging method, DPC does not suffer from speckle artifacts and achieves 2× better resolution than coherent methods. Like all imaging systems, however, DPC is susceptible to aberrations. Here, we propose a method of algorithmic self-calibration for DPC where we simultaneously recover the complex-field of the sample and the spatially-variant aberrations of the system, using 4 images with different illumination source patterns. The resulting phase reconstructions are digitally aberration-corrected.

Wide-field anti-aliased quantitative differential phase contrast microscopy.

Differential phase contrast (DPC) microscopy is a popular methodology to recover quantitative phase information of thin transparent samples under multi-axis asymmetric illumination patterns. Based on spatially partially coherent illuminations, DPC provides high-quality, speckle-free 3D reconstructions with lateral resolution up to twice the coherent diffraction limit, under the precondition that the pixel size of the imaging sensor is small enough to prevent spatial aliasing/undersampling. However, microscope cameras are in general designed to have a large pixel size so that the intensity information transmitted by the optical system cannot be adequately sampled or digitized. On the other hand, using an image sensor with a smaller pixel size or adding a magnification camera adapter to the camera can resolve the undersampling at the expense of a reduced field of view (FOV). To solve this tradeoff, we introduce a new variation of quantitative DPC approach, termed anti-aliased DPC (AADPC), which uses several aliased intensity images under asymmetric illuminations to recover wide-field aliasing-free phase images. Besides, phase transfer functions under different illumination patterns in DPC are analyzed to design an illumination scheme with better phase transfer characteristics. AADPC starts from an initial phase estimate obtained by a DPC-like deconvolution based on the system's weak phase transfer function under discrete half-annular illumination. Then the obtained initial phase map is further refined by the iterative de-multiplexing algorithm to overcome pixel-aliasing and improve the imaging resolution. The data redundancy requirement as well as the optimal illumination scheme of AADPC are analyzed and discussed based on several simulations, suggesting that the spatial undersampling can be mitigated through the iterative algorithm that uses only 4 images, yielding a nearly 4-fold increase in the space-bandwidth product (SBP) compared to the conventional DPC approach. We experimentally verify that AADPC can achieve a half-pitch imaging resolution of 345 nm, corresponding to 1.88× of the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel size. The high-speed, high-throughput quantitative phase imaging capabilities of AADPC are also demonstrated by imaging HeLa cells mitosis in vitro, achieving a full-pitch lateral resolution of 665 nm across a wide FOV of 1.77mm2 at 25 fps.