Conventional Bright-field Microscopy Research Articles

Target-surface multiplexed quantitative dynamic phase microscopic imaging based on the transport-of-intensity equation.

Microscopic phase digital imaging based on the transport of intensity equation, known as TIE, is widely used in optical measurement and biomedical imaging since it can dispense with the dependence of traditional phase imaging systems on mechanical rotational scanning and interferometry devices. In this work, we provide a single exposure target-surface multiplexed phase reconstruction (SETMPR) structure based on TIE, which is remarkably easy to construct since it directly combines a conventional bright-field inverted microscope with a special image plane transmission structure that is capable of wavefront shaping and amplification. In practice, the SETMPR is able to achieve dynamic, non-interferometric, quantitative refractive index distribution of both static optical samples and dynamic biological samples in only one shot, meaning that the only limitation of measuring frequency is the frame rate. By comparing the measurement results of a microlens array and a grating with a standard instrument, the quantitative measurement capability and accuracy are demonstrated. Subsequently, both in situ static and long-term dynamic quantitative imaging of HT22 cells were performed, while automatic image segmentation was completed by introducing machine learning methods, which verified the application prospect of this work in dynamic observation of cellular in the biomedical field.

Quantitative phase imaging comparison of digital holographic microscopy and transport of intensity equation phase through simultaneous measurements of live cells

Quantitative phase imaging (QPI) of live cells allows label-free assessment of cell morphology and quantitative estimation of cell thickness, and therefore volume. Of the techniques available for QPI, digital holographic microscopy (DHM) is an accurate and reliable high-resolution phase imaging technique, but assembly and operation of a DHM capable setup can require significant optical engineering experience and specialized equipment that may not be practical for many labs. Transport of intensity equation (TIE) imaging is a QPI method that is compatible with conventional bright field microscopy, has a lower implementation cost without the need for specialized optics or alignment, and has significantly reduced spatial and temporal coherence requirements when compared to DHM. However, TIE is susceptible to different forms of noise than DHM and its accuracy in live cell imaging has not been well studied. Here, we present a microscope capable of performing simultaneous DHM and TIE phase reconstructions to compare both methods and validate TIE as an accurate phase retrieval method both for a static sample array and for live cells.

Beyond conventional microscopy: Observing kidney tissues by means of fourier ptychography.

Kidney microscopy is a mainstay in studying the morphological structure, physiology and pathology of kidney tissues, as histology provides important results for a reliable diagnosis. A microscopy modality providing at same time high-resolution images and a wide field of view could be very useful for analyzing the whole architecture and the functioning of the renal tissue. Recently, Fourier Ptychography (FP) has been proofed to yield images of biology samples such as tissues and in vitro cells while providing high resolution and large field of view, thus making it a unique and attractive opportunity for histopathology. Moreover, FP offers tissue imaging with high contrast assuring visualization of small desirable features, although with a stain-free mode that avoids any chemical process in histopathology. Here we report an experimental measuring campaign for creating the first comprehensive and extensive collection of images of kidney tissues captured by this FP microscope. We show that FP microscopy unlocks a new opportunity for the physicians to observe and judge renal tissue slides through the novel FP quantitative phase-contrast microscopy. Phase-contrast images of kidney tissue are analyzed by comparing them with the corresponding renal images taken under a conventional bright-field microscope both for stained and unstained tissue samples of different thicknesses. In depth discussion on the advantages and limitations of this new stain-free microscopy modality is reported, showing its usefulness over the classical light microscopy and opening a potential route for using FP in clinical practice for histopathology of kidney.

Multiplane Image Restoration Using Multivariate Curve Resolution: An Alternative Approach to Deconvolution in Conventional Brightfield Microscopy

Three-dimensional reconstruction in brightfield microscopy is challenging since a 2D image includes from in-focus and out-of-focus light which removes the details of the specimen’s structures. To overcome this problem, many techniques exist, but these generally require an appropriate model of Point Spread Function (PSF). Here, we propose a new images restoration method based on the application of Multivariate Curve Resolution (MCR) algorithms to a stack of brightfield microscopy images to achieve 3D reconstruction without the need for PSF. The method is based on a statistical reconstruction approach using a self-modelling mixture analysis. The MCR-ALS (ALS for Alternating Least Square) algorithm under non-negativity constraints, Wiener, Richardson–Lucy, and blind deconvolution algorithms were applied to silica microbeads and red blood cells images. The MCR analysis produces restored images that show informative structures which are not noticeable in the initial images, and this demonstrates its capability for the multiplane reconstruction of the amplitude of 3D objects. In comparison with 3D deconvolution methods based on a set of No Reference Images Quality Metrics (NR-IQMs) that are Standard Deviation, ENTROPY Average Gradient, and Auto Correlation, our method presents better values of these metrics, showing that it can be used as an alternative to 3D deconvolution methods.

Three-dimensional tissue volume generation in conventional brightfield microscopy.

The purpose of the study is to develop and automate a series of steps for enabling digital 3D tissue volume generation in conventional Brightfield microscopy for histopathology applications. Tissue samples were retrieved from the General Hospital of Athens "Hippocration", Greece. Samples were placed on a microtome that produced consecutive 2 μm sections. Each section was stained using Hematoxylin and Eosin and placed on microscope slides. A histopathologist specified the region of interest (ROI) on each slide. A 2D image was created from each ROI using a LEICA DM2500 microscope with a LEICA DFC 420C camera. Τhe 3D volume was created by stacking consecutive 2D images using a deep learning image interpolation method. The reconstructed 3D tissue volumes were evaluated by an expert histopathologist. Results showed that the 3D volumes might reveal information that is not clearly visible or even undetectable in the conventional 2D Brightfield images. In contrast to other 3D tissue imaging technologies, the proposed method (a) does not depend on the distance of the sample from the objectives producing 3D tissue volumes at any desired magnification, (b) does not require a special instrument, it may be implemented with any conventional Brightfield microscope, and (c) can be used for any given routine application, not only for some specialized clinical studies. The proposed study provides the basis for a feasible, cost-less and time-less upgrade of any standard 2D microscope into a 3D imaging instrument that may enhance the quality of diagnostic assessments in histopathology. HIGHLIGHTS: A method for 3D tissue volume generation. 3D volumes reveal information not clearly visible or even undetectable in 2D images. A method for feasible, cost-less and time-less upgrade of any Brightfield 2D microscope into a 3D imaging instrument.

Multimodal Scanning Microscope Combining Optical Coherence Tomography, Raman Spectroscopy and Fluorescence Lifetime Microscopy for Mesoscale Label-Free Imaging of Tissue.

Multimodal optical imaging of tissue has significant potential to become an indispensable diagnostic tool in clinical pathology. Conventional bright-field microscopy provides contrast based on attenuation or reflectance of light, having no depth-related information and no molecular specificity. Recent developments in biomedical optics have introduced a variety of optical modalities, such as Raman spectroscopy (RS), fluorescence lifetime imaging microscopy (FLIM) of endogenous fluorophores, optical coherence tomography (OCT), and others, which provide a distinct characteristic, i.e., molecular, chemical, and morphological information, of the sample. To harvest the full analytical potential of those modalities, we have developed a novel multimodal imaging system, which allows the co-registered acquisition of OCT/FLIM/RS on a single device. The present implementation allows the investigation of biological tissues in the mesoscale range, 0.1-5 mm in a correlated manner. Due to the co-registered acquisition of the modalities, it is possible to directly compare and evaluate the corresponding information between the three modalities. Moreover, by additionally preparing and characterizing entire pathological hematoxylin and eosin (H&E) slides of head and neck biopsies, it is also possible to correlate the multimodal spectroscopic information to any location of the ground truth H&E information. To the best of our knowledge, this is the first development and implementation of a compact and clinically applicable multimodal scanning microscope, which combines OCT, FLIM, and RS together with the possibility for co-registering H&E information for a morpho-chemical tissue characterization and a correlation with the pathological ground truth (H&E) of the underlying signal origin directly in a clinical environment.

Three-dimensional transfer function of optical microscopes in reflection mode.

Three-dimensional (3D) transfer functions build the basis for a comprehensive characterization of optical imaging systems in the spatial frequency domain. Utilizing the projection-slice theorem, the 2D modulation transfer function of an incoherent imaging system can be derived from a 3D transfer function by integration with respect to the axial spatial frequency. For a diffraction limited microscope with homogeneous incoherent pupil illumination, the modulation transfer function equals the 2D autocorrelation function of a circular disc. However, until now to the best of our knowledge no 3D transfer function has been published, which exactly leads to the 2D modulation transfer function of a diffraction limited microscope in reflection mode. In this article, we derive a formula, which after integration with respect to the axial spatial frequency coordinate perfectly fits to the diffraction limited 2D modulation transfer function. The inverse three-dimensional Fourier transform of the 3D transfer function results in a complex-valued 3D point spread function, from which the depth of field, the lateral resolution and, in addition, the corresponding 3D point spread function of both, a conventional and an interference microscope, can beobtained.

Application of convolutional neural networks towards nuclei segmentation in localization-based super-resolution fluorescence microscopy images

BackgroundAutomated segmentation of nuclei in microscopic images has been conducted to enhance throughput in pathological diagnostics and biological research. Segmentation accuracy and speed has been significantly enhanced with the advent of convolutional neural networks. A barrier in the broad application of neural networks to nuclei segmentation is the necessity to train the network using a set of application specific images and image labels. Previous works have attempted to create broadly trained networks for universal nuclei segmentation; however, such networks do not work on all imaging modalities, and best results are still commonly found when the network is retrained on user specific data. Stochastic optical reconstruction microscopy (STORM) based super-resolution fluorescence microscopy has opened a new avenue to image nuclear architecture at nanoscale resolutions. Due to the large size and discontinuous features typical of super-resolution images, automatic nuclei segmentation can be difficult. In this study, we apply commonly used networks (Mask R-CNN and UNet architectures) towards the task of segmenting super-resolution images of nuclei. First, we assess whether networks broadly trained on conventional fluorescence microscopy datasets can accurately segment super-resolution images. Then, we compare the resultant segmentations with results obtained using networks trained directly on our super-resolution data. We next attempt to optimize and compare segmentation accuracy using three different neural network architectures.ResultsResults indicate that super-resolution images are not broadly compatible with neural networks trained on conventional bright-field or fluorescence microscopy images. When the networks were trained on super-resolution data, however, we attained nuclei segmentation accuracies (F1-Score) in excess of 0.8, comparable to past results found when conducting nuclei segmentation on conventional fluorescence microscopy images. Overall, we achieved the best results utilizing the Mask R-CNN architecture.ConclusionsWe found that convolutional neural networks are powerful tools capable of accurately and quickly segmenting localization-based super-resolution microscopy images of nuclei. While broadly trained and widely applicable segmentation algorithms are desirable for quick use with minimal input, optimal results are still found when the network is both trained and tested on visually similar images. We provide a set of Colab notebooks to disseminate the software into the broad scientific community (https://github.com/YangLiuLab/Super-Resolution-Nuclei-Segmentation).

Imaging error compensation method for through-focus scanning optical microscopy images based on deep learning.

Through-focus scanning optical microscopy (TSOM) is a model-based nanoscale metrology technique which combines conventional bright-field microscopy and the relevant numerical simulations. A TSOM image is generated after through-focus scanning and data processing. However, the mechanical vibration and optical noise introduced into the TSOM image during image generation can affect the measurement accuracy. To reduce this effect, this paper proposes a imaging error compensation method for the TSOM image based on deep learning with U-Net. Here, the simulated TSOM image is regarded as the ground truth, and the U-Net is trained using the experimental TSOM images by means of a supervised learning strategy. The experimental TSOM image is first encoded and then decoded with the U-shaped structure of the U-Net. The difference between the experimental and simulated TSOM images is minimised by iteratively updating the weights and bias factors of the network, to obtain the compensated TSOM image. The proposed method is applied for optimising the TSOM images for nanoscale linewidth estimation. The results demonstrate that the proposed method performs as expected and provides a significant enhancement in accuracy.

Low-Coherence Shearing Interferometry With Constant Off-Axis Angle

We present a wide-field interferometric imaging module for biomedical and metrological measurements, employing shearing interferometry with constant off-axis angle (SICA) that can work, for the first time, with a low-coherence light source. In the SICA module, the shearing distance between the interfering beams can be fully controlled without a direct relation with the off-axis angle. In contrast to our previous SICA module, here we use a low-coherence illumination source, providing quantitative phase profiles with significantly lower spatial coherent noise. Although a low-coherence source is used, we obtain off-axis interference on the entire camera sensor, where the optical path difference between the two beams is compensated by using a glass window positioned in the confocal plane. This highly stable, common-path, low-coherence, single-shot interferometric module can be used as an add-on unit to a conventional bright-field microscope illuminated by a low-coherence source. We demonstrate the advantages of using the module by quantitative phase imaging of a polymer bead, fluctuations in a human white blood cell, and dynamics of human sperm cells.

Toward a High-Resolution Reconstruction of 3D Nerve Fiber Architectures and Crossings in the Brain Using Light Scattering Measurements and Finite-Difference Time-Domain Simulations

In many laboratories, conventional bright-field transmission microscopes are available to study the structure and organization principles of fibrous tissue samples, but they usually provide only 2D information. To access the third (out-of-plane) dimension, more advanced techniques are employed. An example is 3D Polarized Light Imaging (3D-PLI), which measures the birefringence of histological brain sections to derive the spatial nerve fiber orientations. Here, we show how light scattering in transmission microscopy measurements can be leveraged to gain 3D structural information about fibrous tissue samples like brain tissue. For this purpose, we developed a simulation framework using finite-difference time-domain (FDTD) simulations and high performance computing, which can easily be adapted to other microscopy techniques and tissue types with comparable fibrous structures (e.g., muscle fibers, collagen, or artificial fibers). As conventional bright-field transmission microscopy provides usually only 2D information about tissue structures, a three-dimensional reconstruction of fibers across several sections is difficult. By combining our simulations with experimental studies, we show that the polarization-independent transmitted light intensity (transmittance) contains 3D information: We demonstrate in several experimental studies on brain sections from different species (rodent, monkey, human) that the transmittance decreases significantly (by more than 50%) with the increasing out-of-plane angle of the nerve fibers. Our FDTD simulations show that this decrease is mainly caused by polarization-independent light scattering in combination with the finite numerical aperture of the imaging system. This allows to use standard transmission microscopy techniques to obtain 3D information about the fiber inclination and to detect steep fibers, without need for additional measurements.

Automatic three-dimensional imaging for blastomere identification in early-stage embryos based on brightfield microscopy

As the first step in manual or automated preimplantation genetic diagnosis (PGD), accurate locating of the blastomere is essential. In order to further improve success rates of the PGD process, it is necessary to obtain three-dimensional information of the blastomeres. In this study, a practical and effective pipeline that allows conventional brightfield microscopy systems to provide 3D imaging feedback for individual blastomeres inside embryos is proposed. The technique consists of two main phases, namely the blastomere identification and the 3D modeling of individual blastomeres. In the first phase, after a series of optical sections are obtained along the z-axis (z-stack), the embryo is located in the z-stack and the blastomere outline is then identified inside the embryo using a coarse-to-fine strategy; In the second phase, a probabilistic model combined with the machine learning approach is designed for the boundary estimation between individual blastomeres, and the 3D coordinate and model of each blastomere are obtained through further relocalization and reconstruction in the z-stack. Experimental results demonstrate that the proposed technique is valid and accurate compared with human perception. Specifically, the proposed technique achieves 90.32% precision rate, and the bias of blastomere position between the proposed method and human segmentation is 1.028 μm.

Cyclin D1 Gene Numerical Imbalances in Laryngeal Squamous Cell Carcinoma: A Tissue Microarray Grid Based Analysis.

Background:Deregulation of critical proteins involved in cell cycle stability, such as cyclins, is a frequent genetic event in the development and progression of solid malignancies. Concerning laryngeal squamous cell carcinoma (LSCC), cyclin D1 oncogenic transformation leads to an aberrant protein expression and seems to affect the biological behaviour of the neoplasm. The aim of this study was to determine the correlation of cyclin D1 numerical imbalances with the corresponding protein expression levels in LSCCs. Material and Method:Using tissue microarray (TMA) technology, fifty (n=50) histologically confirmed primary LSSCs were cored at a diameter of 1.5 mm. Immunohistochemistry (IHC) and chromogenic in situ hybridization (CISH) analyses were applied. Concerning the screening process in CISH slides, a novel real-time reference and calibration grid platform was implemented. Results:Protein overexpression was observed in 22/50 (44%) cases; whereas, gene amplification was seen in 13/50 (26%) cases (p=0.02). Combined protein/ gene deregulation was associated with the stage of malignancy (p= 0.0014, p=0.001), whereas overall protein expression was strongly correlated with the grade of tumour (p= 0.001). Conclusion: Cyclin D1 gene amplification led to aberrant protein expression in LSCCs and it was also correlated with an aggressive biological behaviour. To best of our knowledge, this study was the first described grid based CISH analysis under conventional bright field microscopy for detecting gene numerical imbalances while providing a novel and accurate description for screening-mapping process in the entire slide area.

High-resolution microscopy for imaging cancer pathobiology.

Light microscopy plays an essential role in clinical diagnosis and understanding the pathogenesis of cancer. Conventional bright-field microscope is used to visualize abnormality in tissue architecture and nuclear morphology, but often suffers from many limitations. This review focuses on the potential of new imaging techniques to improve basic and clinical research in pathobiology. Light microscopy has significantly expanded its ability in resolution, imaging volume, speed and contrast. It now allows 3D high-resolution volumetric imaging of tissue architecture from large tissue and molecular structures at nanometer resolution. Pathologists and researchers now have access to various imaging tools to study cancer pathobiology in both breadth and depth. Although clinical adoption of a new technique is slow, the new imaging tools will provide significant new insights and open new avenues for improving early cancer detection, personalized risk assessment and identifying the best treatment strategies.

Photoassisted Electrochemical Micropatterning of Gold Film.

Electrochemical etching is a powerful and popular method for fabricating micropatterns on metal substrates for use in electronic devices, electrochemical sensors, and plasmonic substrates. In order to achieve micropatterning, either a prepatterned insulating layer (mask) or a scanning microelectrode is often required to selectively trigger electrochemical etching at the desired locations. In the present work, we employed a well-focused light beam to enable the photoassisted electrochemical etching of gold film with a spatial resolution close to the optical diffraction limit (∼300 nm). It was found that the simultaneous application of light irradiation and appropriate potential were critical for the oxidative dissolution (i.e., etching) of gold to occur. Superior controllability of light beam allowed for the direct-write micropatterning without the need of mask or probe. Etching kinetics and mechanism were also studied by monitoring the dynamic evolution of optical transparency with a conventional transmission bright-field microscope, together with characterizations on the as-obtained patterns with atomic force microscopy and electron microscopy. This study is anticipated to contribute a feasible method for the micropatterning of gold film with implications for nanoelectronics and electrochemical sensors.

Photoacoustic signal attenuation analysis for the assessment of thin layers thickness in paintings

This study introduces a novel method for the thickness estimation of thin paint layers in works of art, based on photoacoustic signal attenuation analysis (PAcSAA). Ad hoc designed samples with acrylic paint layers (Primary Red Magenta, Cadmium Yellow, Ultramarine Blue) of various thicknesses on glass substrates were realized for the specific application. After characterization by Optical Coherence Tomography imaging, samples were irradiated at the back side using low energy nanosecond laser pulses of 532 nm wavelength. Photoacoustic waves undergo a frequency-dependent exponential attenuation through the paint layer, before being detected by a broadband ultrasonic transducer. Frequency analysis of the recorded time-domain signals allows for the estimation of the average transmitted frequency function, which shows an exponential decay with the layer thickness. Ultrasonic attenuation models were obtained for each pigment and used to fit the data acquired on an inhomogeneous painted mock-up simulating a real canvas painting. Thickness evaluation through PAcSAA resulted in excellent agreement with cross-section analysis with a conventional brightfield microscope. The results of the current study demonstrate the potential of the proposed PAcSAA method for the non-destructive stratigraphic analysis of painted artworks.

Surface plasmon microscopy by spatial light switching for label-free imaging with enhanced resolution.

In this Letter, we describe spatially switched surface plasmon microscopy (ssSPM) based on two-channel momentum sampling. The performance evaluated with periodic nanowires in comparison with conventional SPM and bright-field microscopy shows that the resolution of ssSPM is enhanced by almost 15 times over conventional SPM. ssSPM provides an extremely simple way to attain diffraction limit in SPM and to go beyond for super-resolution in label-free microscopy techniques.

Impact of introducing light-emitting diode fluorescence microscopy services for diagnosis of pulmonary tuberculosis under Revised National Tuberculosis Control Program India.

Context:Light-emitting diode fluorescence microscopy (LED-FM) has been recommended by the WHO and the Government of India over the conventional bright-field microscopy using Ziehl–Neelsen (ZN) staining for the diagnosis of sputum smear-positive tuberculosis (TB) suspects.Aim:The aim of this study was to assess the effectiveness of LED-FM in detecting TB cases.Setting and Design:This retrospective cohort study was carried out in December 2016 using secondary data of the years 2011–2012 from designated microscopy centers (DMCs) at Chandigarh, India.Methodology:Two peripheral DMCs where conventional ZN microscopy was used were taken as controls comparable to two peripheral DMCs which used LED-FM services in programmatic settings. The record of all suspected TB patients who underwent sputum smear examination pre- and post-LED-FM introduction was compared for measuring smear-positive cases, conformational grading, and time taken to read per slide examined. Chi-square was applied to access the statistical significance.Results:Out of total 8850 cases registered after the inception of LED-FM microscopy services, case detection rate was 13.3%, with significant decrease in case detection rate at tertiary level DMCs, there was significant increase in case detection rate at peripheral DMCs operating with LED-FM in contrast to ZN microscopy which was used previously. Scanty grade smear increased significantly by 9.0%. The time taken per slide examination decreased by 57.1% (from 7 min on an average to 3 min on an average) after LED-FM was used.Conclusion:LED-FM is easy to use, takes lesser time to examine slides, and has longer self-life. It also eases laboatory technician's task in reporting scanty grade positives which use to be challenging previously. The results of this study provide enough evidences to scale up the installation process and usage of LED-FM at DMCs for TB diagnosis in Indian settings.

Quantitative assessment of cancer cell morphology and motility using telecentric digital holographic microscopy and machine learning.

The noninvasive, fast acquisition of quantitative phase maps using digital holographic microscopy (DHM) allows tracking of rapid cellular motility on transparent substrates. On two-dimensional surfaces in vitro, MDA-MB-231 cancer cells assume several morphologies related to the mode of migration and substrate stiffness, relevant to mechanisms of cancer invasiveness in vivo. The quantitative phase information from DHM may accurately classify adhesive cancer cell subpopulations with clinical relevance. To test this, cells from the invasive breast cancer MDA-MB-231 cell line were cultured on glass, tissue-culture treated polystyrene, and collagen hydrogels, and imaged with DHM followed by epifluorescence microscopy after staining F-actin and nuclei. Trends in cell phase parameters were tracked on the different substrates, during cell division, and during matrix adhesion, relating them to F-actin features. Support vector machine learning algorithms were trained and tested using parameters from holographic phase reconstructions and cell geometric features from conventional phase images, and used to distinguish between elongated and rounded cell morphologies. DHM was able to distinguish between elongated and rounded morphologies of MDA-MB-231 cells with 94% accuracy, compared to 83% accuracy using cell geometric features from conventional brightfield microscopy. This finding indicates the potential of DHM to detect and monitor cancer cell morphologies relevant to cell cycle phase status, substrate adhesion, and motility. © 2017 International Society for Advancement of Cytometry.

Colloidal motion under the action of a thermophoretic force.

We present thermophoretic measurements in aqueous suspensions of three different polystyrene (PS) particles of varying negative charge, size, and surface coating. Our measurement technique is based on the observation of the colloidal steady-state distribution using conventional bright-field microscopy, which avoids undesirable effects such as laser-induced convection or local heating. We find that the colloids with the weakest zeta potential exhibit the strongest thermophoretic effect, suggesting that the Soret coefficient has a more intricate dependence on surface functionality than predicted by existing theoretical approaches. We also study the relaxation of the colloids to steady-state and propose a model to quantify the relaxation speed, based on the time evolution of the colloidal center of mass. Our observations are well described by this model and show that the relaxation speed tends to increase with the magnitude of the thermophoretic force.