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We present a new approach for retrieving halo-free phase contrast microscopy (hfPC) images by upgrading the conventional PC microscope with an external interferometric module, which generates sufficient data for reversing the halo artifact. Acquiring four independent intensity images, our approach first measures haloed phase maps of the sample. We solve for the halo-free sample transmission function by using a physical model of the image formation under partial spatial coherence. Using this halo-free sample transmission, we can numerically generate artifact-free PC images. Furthermore, this transmission can be further used to obtain quantitative information about the sample, e.g., the thickness with known refractive indices, dry mass of live cells during their cycles. We tested our hfPC method on various control samples, e.g., beads, pillars and validated its potential for biological investigation by imaging live HeLa cells, red blood cells, and neurons.
In this paper we propose a workflow to detect and track mitotic cells in time-lapse microscopy image sequences. In order to avoid the requirement for cell lines expressing fluorescent markers and the associated phototoxicity, phase contrast microscopy is often preferred over fluorescence microscopy in live-cell imaging. However, common specific image characteristics complicate image processing and impede use of standard methods. Nevertheless, automated analysis is desirable due to manual analysis being subjective, biased and extremely time-consuming for large data sets. Here, we present the following workflow based on mathematical imaging methods. In the first step, mitosis detection is performed by means of the circular Hough transform. The obtained circular contour subsequently serves as an initialisation for the tracking algorithm based on variational methods. It is sub-divided into two parts: in order to determine the beginning of the whole mitosis cycle, a backwards tracking procedure is performed. After that, the cell is tracked forwards in time until the end of mitosis. As a result, the average of mitosis duration and ratios of different cell fates (cell death, no division, division into two or more daughter cells) can be measured and statistics on cell morphologies can be obtained. All of the tools are featured in the user-friendly MATLAB®Graphical User Interface MitosisAnalyser.
This paper proposes a nonnegative mix-norm convex optimization method for mitotic cell detection. First, we apply an imaging model-based microscopy image segmentation method that exploits phase contrast optics to extract mitotic candidates in the input images. Then, a convex objective function regularized by mix-norm with nonnegative constraint is proposed to induce sparsity and consistence for discriminative representation of deformable objects in a sparse representation scheme. At last, a Support Vector Machine classifier is utilized for mitotic cell modeling and detection. This method can overcome the difficulty in feature formulation for deformable objects and is independent of tracking or temporal inference model. The comparison experiments demonstrate that the proposed method can produce competing results with the state-of-the-art methods.
Phase contrast time-lapse microscopy is a non-destructive technique that generates large volumes of image-based information to quantify the behaviour of individual cells or cell populations. To guide the development of algorithms for computer-aided cell tracking and analysis, 48 time-lapse image sequences, each spanning approximately 3.5 days, were generated with accompanying ground truths for C2C12 myoblast cells cultured under 4 different media conditions, including with fibroblast growth factor 2 (FGF2), bone morphogenetic protein 2 (BMP2), FGF2 + BMP2, and control (no growth factor). The ground truths generated contain information for tracking at least 3 parent cells and their descendants within these datasets and were validated using a two-tier system of manual curation. This comprehensive, validated dataset will be useful in advancing the development of computer-aided cell tracking algorithms and function as a benchmark, providing an invaluable opportunity to deepen our understanding of individual and population-based cell dynamics for biomedical research.
Replica-based freeze-fracture and freeze-etching electron microscopy methods provide surface topography information, particularly suited to studying membrane protein complexes in their native context. The fidelity and resolution of metal replicas is limited by the inherent property of metal atoms to crystallize. To overcome the limitations of metal replicas, we combined amorphous carbon replicas with phase-contrast electron microscopy. Using this approach, tight junction intramembrane fibrils were shown to have a double stranded morphology.
The ability to image light elements in soft matter at atomic resolution enables unprecedented insight into the structure and properties of molecular heterostructures and beam-sensitive nanomaterials. In this study, we introduce a scanning transmission electron microscopy technique combining a pre-specimen phase plate designed to produce a probe with structured phase with a high-speed direct electron detector to generate nearly linear contrast images with high efficiency. We demonstrate this method by using both experiment and simulation to simultaneously image the atomic-scale structure of weakly scattering amorphous carbon and strongly scattering gold nanoparticles. Our method demonstrates strong contrast for both materials, making it a promising candidate for structural determination of heterogeneous soft/hard matter samples even at low electron doses comparable to traditional phase-contrast transmission electron microscopy. Simulated images demonstrate the extension of this technique to the challenging problem of structural determination of biological material at the surface of inorganic crystals.
Images from cultured lens cells do not convey enough spatial information, and imaging of fixed lens specimens cannot reveal dynamic changes in the cells. As such, a real-time, convenient approach for monitoring label-free imaging of dynamic processes of living cells within the whole lens is urgently needed.
Male infertility is mostly related to semen and spermatozoa, and any diagnosis or treatment requires the investigation of the motility patterns of spermatozoa. The movements of spermatozoa are fast and involve collision and occlusion with each other. In order to extract the motility patterns of spermatozoa, multi-target tracking (MTT) of spermatozoa is necessary. One of the most important steps of MTT is data association, in which the newly arrived observations are used to update the previous tracks. Dynamic Bayesian network (DBN) is a powerful tool for modeling and solving various types of problems such as tracking and classification. There can also be a hybrid-DBN (HDBN), in which both continuous and discrete nodes are present. HDBN has a suitable structure for modeling problems that have both discrete and continuous parameters like MTT. In this research, the data association for MTT of human spermatozoa has been studied. The proposed algorithm was tested over hundreds of manually extracted spermatozoa tracks and evaluated using several standard measures. The superior results of the proposed algorithm in comparison to the other well-known algorithms, show that it could be considered as an improved alternative to traditional computer assisted sperm analysis (CASA) algorithms.
Myxococcus xanthus bacteria are a model system for understanding pattern formation and collective cell behaviors. When starving, cells aggregate into fruiting bodies to form metabolically inert spores. During predation, cells self-organize into traveling cell-density waves termed ripples. Both phase-contrast and fluorescence microscopy are used to observe these patterns but each has its limitations. Phase-contrast images have higher contrast, but the resulting image intensities lose their correlation with cell density. The intensities of fluorescence microscopy images, on the other hand, are well-correlated with cell density, enabling better segmentation of aggregates and better visualization of streaming patterns in between aggregates; however, fluorescence microscopy requires the engineering of cells to express fluorescent proteins and can be phototoxic to cells. To combine the advantages of both imaging methodologies, we develop a generative adversarial network that converts phase-contrast into synthesized fluorescent images. By including an additional histogram-equalized output to the state-of-the-art pix2pixHD algorithm, our model generates accurate images of aggregates and streams, enabling the estimation of aggregate positions and sizes, but with small shifts of their boundaries. Further training on ripple patterns enables accurate estimation of the rippling wavelength. Our methods are thus applicable for many other phenotypic behaviors and pattern formation studies.
The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license.
Phase contrast microscopy allows the study of highly transparent yet detail-rich specimens by producing intensity contrast from phase objects within the sample. Presented here is a generalized phase contrast illumination schema in which condenser optics are entirely abrogated, yielding a condenser-free yet highly effective method of obtaining phase contrast in transmitted-light microscopy. A ring of light emitting diodes (LEDs) is positioned within the light-path such that observation of the objective back focal plane places the illuminating ring in appropriate conjunction with the phase ring. It is demonstrated that true Zernike phase contrast is obtained, whose geometry can be flexibly manipulated to provide an arbitrary working distance between illuminator and sample. Condenser-free phase contrast is demonstrated across a range of magnifications (4-100×), numerical apertures (0.13-1.65NA) and conventional phase positions. Also demonstrated is condenser-free darkfield microscopy as well as combinatorial contrast including Rheinberg illumination and simultaneous, colour-contrasted, brightfield, darkfield and Zernike phase contrast. By providing enhanced and arbitrary working space above the preparation, a range of concurrent imaging and electrophysiological techniques will be technically facilitated. Condenser-free phase contrast is demonstrated in conjunction with scanning ion conductance microscopy (SICM), using a notched ring to admit the scanned probe. The compact, versatile LED illumination schema will further lend itself to novel next-generation transmitted-light microscopy designs. The condenser-free illumination method, using rings of independent or radially-scanned emitters, may be exploited in future in other electromagnetic wavebands, including X-rays or the infrared.
Echinococcus granulosus is a zoonotic parasite with worldwide distribution. The present study focused on comparative morphologic and morphometric observations on the developmental aspects of whole body, more special the reproductive structures of in vitro reared adult worms (RAW) and in vivo reared adult worms in definitive host (AWIDH) using differential interference contrast (DIC)/Nomarski, phase contrast and routine optical microscopy.
Recent studies at high magnetic fields using the phase of gradient-echo MR images have shown the ability to unveil cortical substructure in the human brain. To investigate the contrast mechanisms in phase imaging, this study extends, for the first time, phase imaging to the rodent brain. Using a 14.1 T horizontal bore animal MRI scanner for in vivo micro-imaging, images with an in-plane resolution of 33 microm were acquired. Phase images revealed, often more clearly than the corresponding magnitude images, hippocampal fields, cortical layers (e.g. layer 4), cerebellar layers (molecular and granule cell layers) and small white matter structures present in the striatum and septal nucleus. The contrast of the phase images depended in part on the orientation of anatomical structures relative to the magnetic field, consistent with bulk susceptibility variations between tissues. This was found not only for vessels, but also for white matter structures, such as the anterior commissure, and cortical layers in the cerebellum. Such susceptibility changes could result from variable blood volume. However, when the deoxyhemoglobin content was reduced by increasing cerebral blood flow (CBF) with a carbogen breathing challenge, contrast between white and gray matter and cortical layers was not affected, suggesting that tissue cerebral blood volume (and therefore deoxyhemoglobin) is not a major source of the tissue phase contrast. We conclude that phase variations in gradient-echo images are likely due to susceptibility shifts of non-vascular origin.
The problem of automated segmenting and tracking of the outlines of cells in microscope images is the subject of active research. While great progress has been made on recognizing cells that are of high contrast and of predictable shape, many situations arise in practice where these properties do not exist and thus many interesting potential studies - such as the migration patterns of astrocytes to scratch wounds - have been relegated to being largely qualitative in nature. Here we analyse a select number of recent developments in this area, and offer an algorithm based on parametric active contours and formulated by taking into account cell movement dynamics. This Cell-Derived Active Contour (CDAC) method is compared with two state-of-the-art segmentation methods for phase-contrast microscopy. Specifically, we tackle a very difficult segmentation problem: human astrocytes that are very large, thin, and irregularly-shaped. We demonstrate quantitatively better results for CDAC as compared to similar segmentation methods, and we also demonstrate the reliable segmentation of qualitatively different data sets that were not possible using existing methods. We believe this new method will enable new and improved automatic cell migration and movement studies to be made.
In 1934, Frits Zernike demonstrated that it is possible to exploit the sample's refractive index to obtain superior contrast images of biological cells. The refractive index contrast of a cell surrounded by media yields a change in the phase and intensity of the transmitted light wave. This change can be due to either scattering or absorption caused by the sample. Most cells are transparent at visible wavelengths, which means the imaginary component of their complex refractive index, also known as extinction coefficient k, is close to zero. Here, we explore the use of c-band ultra-violet (UVC) light for high-contrast high-resolution label-free microscopy, as k is naturally substantially higher in the UVC than at visible wavelengths. Using differential phase contrast illumination and associated processing, we achieve a 7- to 300-fold improvement in contrast compared to visible-wavelength and UVA differential interference contrast microscopy or holotomography, and quantify the extinction coefficient distribution within liver sinusoidal endothelial cells. With a resolution down to 215 nm, we are, for the first time in a far-field label-free method, able to image individual fenestrations within their sieve plates which normally requires electron or fluorescence superresolution microscopy. UVC illumination also matches the excitation peak of intrinsically fluorescent proteins and amino acids and thus allows us to utilize autofluorescence as an independent imaging modality on the same setup.
Because of its non-destructive nature, label-free imaging is an important strategy for studying biological processes. However, routine microscopic techniques like phase contrast or DIC suffer from shadow-cast artifacts making automatic segmentation challenging. The aim of this study was to compare the segmentation efficacy of published steps of segmentation work-flow (image reconstruction, foreground segmentation, cell detection (seed-point extraction) and cell (instance) segmentation) on a dataset of the same cells from multiple contrast microscopic modalities.
Phase contrast microscopy has played a central role in the development of modern biology, geology, and nanotechnology. It can visualize the structure of translucent objects that remains hidden in regular optical microscopes. The optical layout of a phase contrast microscope is based on a 4 f image processing setup and has essentially remained unchanged since its invention by Zernike in the early 1930s. Here, we propose a conceptually new approach to phase contrast imaging that harnesses the non-local optical response of a guided-mode-resonator metasurface. We highlight its benefits and demonstrate the imaging of various phase objects, including biological cells, polymeric nanostructures, and transparent metasurfaces. Our results showcase that the addition of this non-local metasurface to a conventional microscope enables quantitative phase contrast imaging with a 0.02π phase accuracy. At a high level, this work adds to the growing body of research aimed at the use of metasurfaces for analog optical computing.
The electron density resolution is 1000 times higher for synchrotron-radiation phase-contrast CT imaging than conventional X-ray absorption imaging in light elements, with which high-resolution X-ray imaging of biological soft tissue can be achieved. In the present study, we used phase-contrast X-ray CT to investigate human resected esophagus and esophageal carcinoma specimens. This technology revealed the three-layer structure of the esophageal wall-- mucous, submucosa and muscular layers. The mucous and muscular layers were clearly separated by a loose submucosa layer with a honeycomb appearance. The surface of the mucous layer was smooth. In esophageal carcinoma, because of tumor tissue infiltration, the submucosa layer was absent, which indicated destruction of the submucosa. The boundary between normal tissue and tumor was comparatively fuzzy, the three-layer structure of the esophageal wall was indistinct. The surface of the mucous layer was rugose. The technology might be helpful in tumor staging of esophageal carcinoma.
X-ray computed tomography of small animals and their organs is an essential tool in basic and preclinical biomedical research. In both phase-contrast and absorption tomography high spatial resolution and short exposure times are of key importance. However, the observable spatial resolutions and achievable exposure times are presently limited by system parameters rather than more fundamental constraints like, e.g., dose. Here we demonstrate laboratory tomography with few-ten μm spatial resolution and few-minute exposure time at an acceptable dose for small-animal imaging, both with absorption contrast and phase contrast. The method relies on a magnifying imaging scheme in combination with a high-power small-spot liquid-metal-jet electron-impact source. The tomographic imaging is demonstrated on intact mouse, phantoms and excised lungs, both healthy and with pulmonary emphysema.
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