Quantitative Phase Imaging Method Research Articles

Hybrid brightfield and darkfield transport of intensity approach for high-throughput quantitative phase microscopy

Transport of intensity equation (TIE) is a well-established non-interferometric phase retrieval approach that enables quantitative phase imaging (QPI) by simply measuring intensity images at multiple axially displaced planes. The advantage of a TIE-based QPI system is its compatibility with partially coherent illumination, which provides speckle-free imaging with resolution beyond the coherent diffraction limit. However, TIE is generally implemented with a brightfield (BF) configuration, and the maximum achievable imaging resolution is still limited to the incoherent diffraction limit (twice the coherent diffraction limit). It is desirable that TIE-related approaches can surpass this limit and achieve high-throughput [high-resolution and wide field of view (FOV)] QPI. We propose a hybrid BF and darkfield transport of intensity (HBDTI) approach for high-throughput quantitative phase microscopy. Two through-focus intensity stacks corresponding to BF and darkfield illuminations are acquired through a low-numerical-aperture (NA) objective lens. The high-resolution and large-FOV complex amplitude (both quantitative absorption and phase distributions) can then be synthesized based on an iterative phase retrieval algorithm taking the coherence model decomposition into account. The effectiveness of the proposed method is experimentally verified by the retrieval of the USAF resolution target and different types of biological cells. The experimental results demonstrate that the half-width imaging resolution can be improved from 1230 nm to 488 nm with 2.5 × expansion across a 4 × FOV of 7.19 mm2, corresponding to a 6.25 × increase in space-bandwidth product from ∼5 to ∼30.2 megapixels. In contrast to conventional TIE-based QPI methods where only BF illumination is used, the synthetic aperture process of HBDTI further incorporates darkfield illuminations to expand the accessible object frequency, thereby significantly extending the maximum available resolution from 2NA to ∼5NA with a ∼5 × promotion of the coherent diffraction limit. Given its capability for high-throughput QPI, the proposed HBDTI approach is expected to be adopted in biomedical fields, such as personalized genomics and cancer diagnostics.

Comparison of common-path off-axis digital holography and transport of intensity equation in quantitative phase measurement

The quantitative phase imaging methods based on digital holography (DH) and transport of intensity equation (TIE) are both popular high-resolution computational imaging techniques with broad applications. In contrast, the results of TIE often lack reliability, while those of DH are always regarded as the standard for phase measurements. Is DH more reliable and accurate than TIE in all cases? Here, we fully compare and analysis some common factors of conventional FFT-based TIE method and common-path off-axis DH method in quantitative phase measurements, such as the grayscale of recorded image (or hologram), effective measurement area, temporal stability, noise and the focal plane offset. By measuring some standard (microlens array and cake structure) and unknown samples (HT22 cells and fiber microstructure), the effects of different factors can be clearly quantified and illustrated. As a result, the DH method mainly suffers from the serious coherent noise and poor temporal stability, and the TIE method has a huge error when several factors are not selected properly, which explains its unreliability. Comparatively speaking, the TIE method can achieve better results with appropriate parameters.

Quantitative phase imaging based on model transfer learning.

Convolutional neural networks have been widely used in optical information processing and the generalization ability of the network depends greatly on the scale and diversity of the datasets, however, the acquisition of mass datasets and later annotation have become a common problem that hinders its further progress. In this study, a model transfer-based quantitative phase imaging (QPI) method is proposed, which fine-tunes the network parameters through loading pre-training base model and transfer learning, enable the network with good generalization ability. Most importantly, a feature fusion method based on moment reconstruction is proposed for training dataset generation, which can construct rich enough datasets that can cover most situations and accurately annotated, it fundamentally solves the problem from the scale and representational ability of the datasets. Besides, a feature distribution distance scoring (FDDS) rule is proposed to evaluate the rationality of the constructed datasets. The experimental results show that this method is suitable for different types of samples to achieve fast and high-accuracy phase imaging, which greatly relieves the pressure of data, tagging and generalization ability in the data-driven method.

Coherence-encoded synthetic aperture for super-resolution quantitative phase imaging

Quantitative phase imaging (QPI) has quickly established its role in identifying rare events and screening in biomedicine or automated image data analysis using artificial intelligence. These and many other applications share the requirement for extensive high-quality datasets, which is challenging to meet because the invariance of the space–bandwidth product (SBP) fundamentally limits the microscope system throughput. Here, we present a method to overcome the SBP limit by achieving QPI super-resolution using a synthetic aperture approach in a holographic microscope with a partially coherent broad source illumination. We exploit intrinsic coherence-gating properties of the partially coherent light combined with the oblique illumination provided by the diffraction on a simple phase grating placed in proximity of the specimen. We sequentially coherence gate the light scattered into each grating’s diffraction order, and we use the acquired images to synthesize QPI with significantly increased spatial frequency bandwidth. The resolution of QPI is increased substantially beyond Abbe’s diffraction limit while a large field of view of low numerical aperture objectives is kept. This paper presents a thorough theoretical treatment of the coherence-gated imaging process supplemented by a detailed measurement methodology. The capability of the proposed method is demonstrated by imaging a phase resolution target and biological specimens. We envision our work providing an easily implementable super-resolution QPI method particularly suitable for high-throughput biomedical applications.

Single-shot TIE using polarization multiplexing (STIEP) for quantitative phase imaging

Transport of intensity equation (TIE) is a promising technique for quantitative phase imaging (QPI). Usually, in TIE, two axially defocused intensity distributions are used to recover the phase, which requires the mechanical shift of either the image sensor or tested sample along the optical axis. This paper presents a new method for QPI based on single-shot TIE using polarization multiplexing. The two defocused intensity distributions are recorded simultaneously on a single camera plane. For that, a diffractive optical element is positioned at the Fourier plane of the sample to split the incoming wavefront into two orthogonally polarized wavefronts. These multiplexed wavefronts will result in two axially and symmetrically defocused intensities on the camera plane. Furthermore, the technique is well-suited for both static and dynamic phase measurements, including that of biological samples (e.g., red blood cells). The feasibility of the proposed method is demonstrated with experimental results.

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.

Multimodal FACED imaging for large-scale single-cell morphological profiling

Free-space angular-chirp-enhanced delay (FACED) is an ultrafast laser-scanning technique that allows for high imaging speed at the scale orders of magnitude greater than the current technologies. However, this speed advantage has only been restricted to bright-field and fluorescence imaging—limiting the variety of image contents and hindering its applicability in image-based bioassay, which increasingly demands rich phenotypic readout at a large scale. Here, we present a new high-speed quantitative phase imaging (QPI) based on time-interleaved phase-gradient FACED image detection. We further integrate this system with a microfluidic flow cytometer platform that enables synchronized and co-registered single-cell QPI and fluorescence imaging at an imaging throughput of 77 000 cells/s with sub-cellular resolution. Combined with deep learning, this platform empowers comprehensive image-based profiling of single-cell biophysical phenotypes that can offer not only sufficient label-free power for cell-type classification but also cell-cycle phase tracking with high accuracy comparable to the gold-standard fluorescence method. This platform further enables correlative, compartment-specific single-cell analysis of the spatially resolved biophysical profiles at the throughput inaccessible with existing QPI methods. The high imaging throughput and content given by this multimodal FACED imaging system could open new opportunities in image-based single-cell analysis, especially systematic analysis that correlates the biophysical and biochemical information of cells, and provide new mechanistic insights into biophysical heterogeneities in many biological processes.

Variations of intracellular density during the cell cycle arise from tip-growth regulation in fission yeast.

Intracellular density impacts the physical nature of the cytoplasm and can globally affect cellular processes, yet density regulation remains poorly understood. Here, using a new quantitative phase imaging method, we determined that dry-mass density in fission yeast is maintained in a narrow distribution and exhibits homeostatic behavior. However, density varied during the cell cycle, decreasing during G2, increasing in mitosis and cytokinesis, and dropping rapidly at cell birth. These density variations were explained by a constant rate of biomass synthesis, coupled to slowdown of volume growth during cell division and rapid expansion post-cytokinesis. Arrest at specific cell-cycle stages exacerbated density changes. Spatially heterogeneous patterns of density suggested links between density regulation, tip growth, and intracellular osmotic pressure. Our results demonstrate that systematic density variations during the cell cycle are predominantly due to modulation of volume expansion, and reveal functional consequences of density gradients and cell-cycle arrests.

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.

Non-interferometric accurate phase imaging via linear-convergence iterative optimization

This paper reported a general non-interferometric high-accuracy quantitative phase imaging (QPI) method for arbitrary complex-valued objects. Given by a typical 4-f optical configuration as the imaging system, three frames of small-window phase modulation are applied on the object's Fourier spectrum so that redistributed intensity patterns are produced on the image plane, in which the object phase emerges at different degree. Then, an algebraic relationship that connects the object phase with the output intensity is established to provide us with an approximate closed-form phase recovery. Further, an efficient iterative optimization strategy is developed to turn that approximate solution into an accurate one. Due to the linear convergence property of the iteration, a high-accuracy phase recovery is achieved without requiring heavy iterations. The feasibility and accuracy of the proposed method are verified by both numerical simulations and experiments on diverse phase objects including biomedical tissues.

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.

Quantitative phase microscopy imaging based on fractional spiral phase plate

Quantitative phase imaging (QPI), which combines phase imaging with optical microscopy technology, provides a marker-free, fast, non-destructive, and high-resolution imaging method for observing transparent biological samples. It is widely used in life science, biomedicine, etc. As an emerging QPI technology, spiral phase contrast microscopy (SPCM) uses a spiral phase filter to achieve edge enhancement of amplitude or phase objects. Using the multi-step phase-shifting technology, a complex sample can be measured quantitatively, which has the advantages of high stability, high sensitivity and high precision. However, the SPCM requires at least three-step phase-shifted spiral phase filtered images to achieve the quantitative reconstruction of the amplitude and phase of a sample, and the image acquisition process and the reconstruction process are relatively complicated, which require high stability of system, and the SPCM has low temporal resolution. In order to further improve the performance of SPCM and increase the system stability, sensitivity and temporal resolution, in this paper a quantitative phase imaging method and system based on a fractional spiral phase plate is proposed. Through a sample intensity image filtered by a fractional spiral phase plate, the modified Gerchberg-Saxton iterative phase retrieval algorithm is used to quantitatively reconstruct the phase of a pure phase sample, which simplifies the experimental process and phase reconstruction steps of spiral phase contrast microsocopy. In the computer simulation experiments, the phase imaging process and the reconstruction process of spiral phase plates based on different topological charges are studied, the feasibility of which is analyzed. Finally, through imaging and phase reconstruction of the phase grating and biological cell sample, it is verified that the phase contrast microscopy method based on the fractional spiral phase plate can effectively improve the contrast of spiral phase contrast microscopy and can obtain a quantitative reconstruciton of a weak phase object. The phase information of a sample has significance in research and application for developing the spiral phase contrast microscopy.

Phase-sensitive, angle-resolved light-scattering microscopy of single cells.

We report what is to our knowledge the first use of Fourier phase microscopy (FPM) to estimate diameters of individual single-micrometer beads and to classify cells based upon changes in scatterer size distribution. FPM, a quantitative phase imaging (QPI) method, combines the planar illumination typically used in off-axis QPI (ideal for Mie theory analysis) with the common-path geometry typically used in on-axis QPI (ideal for optimizing angular scattering range). Low-spatial-frequency imaging artifacts inherent to FPM have negligible impact upon these angular-domain applications. The system is simple to align and stable, and requires no external reference beam. Angular scattering patterns obtained from single 1 µm polystyrene beads in glycerol (Δn=0.11) display unprecedented fidelity to Mie theory, produce diameter estimates consistent with the manufacturer's specifications, and offer precision on the scale of tens of nanometers. Measurements of macrophages at different stages of antibody-dependent cellular phagocytosis demonstrate the ability to detect changes in a cell's scattering caused by the presence of phagocytosed material within.

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.

Quantitative phase imaging in dual-wavelength interferometry using a single wavelength illumination and deep learning.

In this manuscript, we propose a quantitative phase imaging method based on deep learning, using a single wavelength illumination to realize dual-wavelength phase-shifting phase recovery. By using the conditional generative adversarial network (CGAN), from one interferogram recorded at a single wavelength, we obtain interferograms at other wavelengths, the corresponding wrapped phases and then the phases at synthetic wavelengths. The feasibility of the proposed method is verified by simulation and experiments. The results demonstrate that the measurement range of single-wavelength interferometry (SWI) is improved by keeping a simple setup, avoiding the difficulty caused by using two wavelengths simultaneously. This will provide an effective solution for the problem of phase unwrapping and the measurement range limitation in phase-shifting interferometry.

High-resolution label-free imaging of tissue morphology with confocal phase microscopy

Label-free imaging approaches seek to simplify and augment histopathologic assessment by replacing the current practice of staining by dyes to visualize tissue morphology with quantitative optical measurements. Quantitative phase imaging (QPI) operates with visible/UV light and thus provides a resolution matched to current practice. Here we introduce and demonstrate confocal QPI for label-free imaging of tissue sections and assess its utility for manual histopathologic inspection. Imaging cancerous and normal adjacent human breast and prostate, we show that tissue structural organization can be resolved with high spatial detail comparable to conventional hematoxylin and eosin (H&E) stains. Our confocal QPI images are found to be free of halo, solving this common problem in QPI. We further describe a virtual imaging system based on finite-difference time-domain (FDTD) calculations and combine it with numerical tissue phantoms to quantitatively show the absence of halo and the improved clarity in resolving subcellular features with confocal QPI compared to wide-field QPI. Confocal QPI bears the potential to become a common tool for label-free disease diagnosis, while the presented FDTD method provides a flexible platform to evaluate the diagnostic potential of QPI methods.

Advantages of Fresnel biprism-based digital holographic microscopy in quantitative phase imaging.

.Significance: The hallmarks of digital holographic microscopy (DHM) compared with other quantitative phase imaging (QPI) methods are high speed, accuracy, spatial resolution, temporal stability, and polarization-sensitivity (PS) capability. The above features make DHM suitable for real-time quantitative PS phase imaging in a broad number of biological applications aimed at understanding cell growth and dynamic changes occurring during physiological processes and/or in response to pharmaceutical agents.Aim: The insertion of a Fresnel biprism (FB) in the image space of a light microscope potentially turns any commercial system into a DHM system enabling QPI with the five desired features in QPI simultaneously: high temporal sensitivity, high speed, high accuracy, high spatial resolution, and PS. To the best of our knowledge, this is the first FB-based DHM system providing these five features all together.Approach: The performance of the proposed system was calibrated with a benchmark phase object. The PS capability has been verified by imaging human U87 glioblastoma cells.Results: The proposed FB-based DHM system provides accurate phase images with high spatial resolution. The temporal stability of our system is in the order of a few nanometers, enabling live-cell studies. Finally, the distinctive behavior of the cells at different polarization angles (e.g., PS capability) can be observed with our system.Conclusions: We have presented a method to turn any commercial light microscope with monochromatic illumination into a PS QPI system. The proposed system provides accurate quantitative PS phase images in a new, simple, compact, and cost-effective format, thanks to the low cost (a few hundred dollars) involved in implementing this simple architecture, enabling the use of this QPI technique accessible to most laboratories with standard light microscopes.

High-resolution quantitative phase imaging based on a spatial light modulator and incremental binary random sampling.

We propose a single-beam high-resolution quantitative phase imaging method based on a spatial light modulator (SLM) and an incremental binary random sampling (IBRS) algorithm. In this method, the image of the test object presents on the image sensor through an optical microscopy system composed of an objective lens and a collimating lens. A transmittance SLM displaying a group of well-designed IBRS patterns is inserted in the optical microscopy system to modulate the object wavefront. The phase information of the object image can be quantitatively retrieved from the recorded intensities using the IBRS algorithm and the amplitude obtained directly from the diffraction intensity. The IBRS algorithm employed in our method has higher accuracy for phase retrieval compared with our previously proposed complementary random sampling algorithm, which is confirmed by simulations. Further, we demonstrate experimentally the feasibility of our method through several examples: phase imaging of immersion oil droplets with a diffraction-limited lateral resolution of 1.54 µm and a few microbiological specimens with 0.70 µm. Experimental results reveal that our proposed method provides a feasible single-beam technique for quantitative phase imaging with a high spatial resolution.

NEW POSSIBILITIES OF STRUCTURAL MORPHOLOGICAL PECULIARITIES INVESTIGATION BY QUANTITATIVE PHASE IMAGING METHOD

The possibility of quantitative phase imaging method for the assessment of structural morphological erythrocytes peculiarities under normal and stress conditions were studied. It is stated that quantitative phase imaging is an important instrument which allows to visualize red blood cells. New aspects of stress influence on functional cells morphology are defined.

3D-printed biological cell phantom for testing 3D quantitative phase imaging systems

As the 3D quantitative phase imaging (QPI) methods mature, their further development calls for reliable tools and methods to characterize and compare their metrological parameters. We use refractive index engineering during two-photon laser photolithography to fabricate a life-scale phantom of a biological cell with internal structures that mimic optical and structural properties of mammalian cells. After verification with a number of reference techniques, the phantom is used to characterize the performance of a limited-angle holographic tomography microscope.