Showing papers in "Journal of Microscopy in 2015"

High-resolution, high-throughput imaging with a multibeam scanning electron microscope.

Abstract: Electron-electron interactions and detector bandwidth limit the maximal imaging speed of single-beam scanning electron microscopes. We use multiple electron beams in a single column and detect secondary electrons in parallel to increase the imaging speed by close to two orders of magnitude and demonstrate imaging for a variety of samples ranging from biological brain tissue to semiconductor wafers.

Review of free software tools for image analysis of fluorescence cell micrographs

Abstract: An increasing number of free software tools have been made available for the evaluation of fluorescence cell micrographs. The main users are biologists and related life scientists with no or little knowledge of image processing. In this review, we give an overview of available tools and guidelines about which tools the users should use to segment fluorescence micrographs. We selected 15 free tools and divided them into stand-alone, Matlab-based, ImageJ-based, free demo versions of commercial tools and data sharing tools. The review consists of two parts: First, we developed a criteria catalogue and rated the tools regarding structural requirements, functionality (flexibility, segmentation and image processing filters) and usability (documentation, data management, usability and visualization). Second, we performed an image processing case study with four representative fluorescence micrograph segmentation tasks with figure-ground and cell separation. The tools display a wide range of functionality and usability. In the image processing case study, we were able to perform figure-ground separation in all micrographs using mainly thresholding. Cell separation was not possible with most of the tools, because cell separation methods are provided only by a subset of the tools and are difficult to parametrize and to use. Most important is that the usability matches the functionality of a tool. To be usable, specialized tools with less functionality need to fulfill less usability criteria, whereas multipurpose tools need a well-structured menu and intuitive graphical user interface.

Developing 3D SEM in a broad biological context.

Abstract: When electron microscopy (EM) was introduced in the 1930s it gave scientists their first look into the nanoworld of cells. Over the last 80 years EM has vastly increased our understanding of the complex cellular structures that underlie the diverse functions that cells need to maintain life. One drawback that has been difficult to overcome was the inherent lack of volume information, mainly due to the limit on the thickness of sections that could be viewed in a transmission electron microscope (TEM). For many years scientists struggled to achieve three-dimensional (3D) EM using serial section reconstructions, TEM tomography, and scanning EM (SEM) techniques such as freeze-fracture. Although each technique yielded some special information, they required a significant amount of time and specialist expertise to obtain even a very small 3D EM dataset. Almost 20 years ago scientists began to exploit SEMs to image blocks of embedded tissues and perform serial sectioning of these tissues inside the SEM chamber. Using first focused ion beams (FIB) and subsequently robotic ultramicrotomes (serial block-face, SBF-SEM) microscopists were able to collect large volumes of 3D EM information at resolutions that could address many important biological questions, and do so in an efficient manner. We present here some examples of 3D EM taken from the many diverse specimens that have been imaged in our core facility. We propose that the next major step forward will be to efficiently correlate functional information obtained using light microscopy (LM) with 3D EM datasets to more completely investigate the important links between cell structures and their functions.

Computational microscopic imaging for malaria parasite detection: a systematic review

Abstract: Malaria, being an epidemic disease, demands its rapid and accurate diagnosis for proper intervention. Microscopic image-based characterization of erythrocytes plays an integral role in screening of malaria parasites. In practice, microscopic evaluation of blood smear image is the gold standard for malaria diagnosis; where the pathologist visually examines the stained slide under the light microscope. This visual inspection is subjective, error-prone and time consuming. In order to address such issues, computational microscopic imaging methods have been given importance in recent times in the field of digital pathology. Recently, such quantitative microscopic techniques have rapidly evolved for abnormal erythrocyte detection, segmentation and semi/fully automated classification by minimizing such diagnostic errors for computerized malaria detection. The aim of this paper is to present a review on enhancement, segmentation, microscopic feature extraction and computer-aided classification for malaria parasite detection.

Challenges of microtome-based serial block-face scanning electron microscopy in neuroscience.

Abstract: Serial block‐face scanning electron microscopy (SBEM) is becoming increasingly popular for a wide range of applications in many disciplines from biology to material sciences. This review focuses on applications for circuit reconstruction in neuroscience, which is one of the major driving forces advancing SBEM. Neuronal circuit reconstruction poses exceptional challenges to volume EM in terms of resolution, field of view, acquisition time and sample preparation. Mapping the connections between neurons in the brain is crucial for understanding information flow and information processing in the brain. However, information on the connectivity between hundreds or even thousands of neurons densely packed in neuronal microcircuits is still largely missing. Volume EM techniques such as serial section TEM, automated tape‐collecting ultramicrotome, focused ion‐beam scanning electron microscopy and SBEM (microtome serial block‐face scanning electron microscopy) are the techniques that provide sufficient resolution to resolve ultrastructural details such as synapses and provides sufficient field of view for dense reconstruction of neuronal circuits. While volume EM techniques are advancing, they are generating large data sets on the terabyte scale that require new image processing workflows and analysis tools. In this review, we present the recent advances in SBEM for circuit reconstruction in neuroscience and an overview of existing image processing and analysis pipelines.

Methods to calibrate and scale axial distances in confocal microscopy as a function of refractive index

Abstract: Accurate distance measurement in 3D confocal microscopy is important for quantitative analysis, volume visualization and image restoration. However, axial distances can be distorted by both the point spread function (PSF) and by a refractive-index mismatch between the sample and immersion liquid, which are difficult to separate. Additionally, accurate calibration of the axial distances in confocal microscopy remains cumbersome, although several high-end methods exist. In this paper we present two methods to calibrate axial distances in 3D confocal microscopy that are both accurate and easily implemented. With these methods, we measured axial scaling factors as a function of refractive-index mismatch for high-aperture confocal microscopy imaging. We found that our scaling factors are almost completely linearly dependent on refractive index and that they were in good agreement with theoretical predictions that take the full vectorial properties of light into account. There was however a strong deviation with the theoretical predictions using (high-angle) geometrical optics, which predict much lower scaling factors. As an illustration, we measured the PSF of a correctly calibrated point-scanning confocal microscope and showed that a nearly index-matched, micron-sized spherical object is still significantly elongated due to this PSF, which signifies that care has to be taken when determining axial calibration or axial scaling using such particles.

Making EBSD on water ice routine.

Abstract: Electron backscatter diffraction (EBSD) on ice is a decade old. We have built upon previous work to select and develop methods of sample preparation and analysis that give >90% success rate in obtaining high-quality EBSD maps, for the whole surface area (potentially) of low porosity (

3D imaging of cement-based materials at submicron resolution by combining laser scanning confocal microscopy with serial sectioning

Abstract: In this paper, we present a new method to reconstruct large volumes of nontransparent porous materials at submicron resolution. The proposed method combines fluorescence laser scanning confocal microscopy with serial sectioning to produce a series of overlapping confocal z-stacks, which are then aligned and stitched based on phase correlation. The method can be extended in the XY plane to further increase the overall image volume. Resolution of the reconstructed image volume does not degrade with increase in sample size. We have used the method to image cementitious materials, hardened cement paste and concrete and the results obtained show that the method is reliable. Possible applications of the method such as three-dimensional characterization of the pores and microcracks in hardened concrete, three-dimensional particle shape characterization of cementitious materials and three-dimensional characterization of other porous materials such as rocks and bioceramics are discussed.

Automated system for characterization and classification of malaria-infected stages using light microscopic images of thin blood smears.

Abstract: Summary In this paper, we propose a comprehensive image characterization cum classification framework for malaria-infected stage detection using microscopic images of thin blood smears. The methodology mainly includes microscopic imaging of Leishman stained blood slides, noise reduction and illumination correction, erythrocyte segmentation, feature selection followed by machine classification. Amongst three-image segmentation algorithms (namely, rule-based, Chan–Vese-based and marker-controlled watershed methods), marker-controlled watershed technique provides better boundary detection of erythrocytes specially in overlapping situations. Microscopic features at intensity, texture and morphology levels are extracted to discriminate infected and noninfected erythrocytes. In order to achieve subgroup of potential features, feature selection techniques, namely, F-statistic and information gain criteria are considered here for ranking. Finally, five different classifiers, namely, Naive Bayes, multilayer perceptron neural network, logistic regression, classification and regression tree (CART), RBF neural network have been trained and tested by 888 erythrocytes (infected and noninfected) for each features’ subset. Performance evaluation of the proposed methodology shows that multilayer perceptron network provides higher accuracy for malaria-infected erythrocytes recognition and infected stage classification. Results show that top 90 features ranked by F-statistic (specificity: 98.64%, sensitivity: 100%, PPV: 99.73% and overall accuracy: 96.84%) and top 60 features ranked by information gain provides better results (specificity: 97.29%, sensitivity: 100%, PPV: 99.46% and overall accuracy: 96.73%) for malaria-infected stage classification. Lay Description Malaria, being a mosquito-borne disease, is triggered by a parasite. In general, it causes fever, chills, and flu-like illness. It is transmitted from one infected patient to a healthy individual through bite of infected female Anopheles mosquito. Plasmodium parasite species are solely responsible for malaria attack. In reality, there are four types of Plasmodium parasites (Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae, Plasmodium ovale). Plasmodium falciparum (P. falciparum) and Plasmodium vivax (P. vivax) are the common infection types observed in the world population. P. falciparum is more deadly than P. vivax. It is considered as an epidemic disease due to its outbreak over one or more populations. In this situation, if malaria is late diagnosed, left undiagnosed and untreated as well, it may develop severe complications and even die. In view of this, an efficient and rapid diagnostic method is essential. The most common and frequent diagnostic test is manual evaluation of microscopic images of peripheral blood smears. It, in fact, involves lot of ambiguity and inter-observer variability leading to diagnostic error. In addition, sometimes even clinicians are not available in time. In view of this, we aim to automate the microscopic image evaluation process of thin blood smears without human intervention under medical image analytics cum classification framework. From the microscopic images, erythrocytes (parasite infected and non-infected) are automatically segmented and quantified using intensity, texture and morphology based characteristics. Mathematical measures are adopted to select good (discriminative in nature) features in order to accelerate system's performance. Our results establish that information gain based multilayer perceptron neural network achieves the highest accuracy using minimum number of good features in comparison with other feature selection cum classifiers combinations.

Correlation of two-photon in vivo imaging and FIB/SEM microscopy.

Abstract: Advances in the understanding of brain functions are closely linked to the technical developments in microscopy. In this study, we describe a correlative microscopy technique that offers a possibility of combining two-photon in vivo imaging with focus ion beam/scanning electron microscope (FIB/SEM) techniques. Long-term two-photon in vivo imaging allows the visualization of functional interactions within the brain of a living organism over the time, and therefore, is emerging as a new tool for studying the dynamics of neurodegenerative diseases, such as Alzheimer's disease. However, light microscopy has important limitations in revealing alterations occurring at the synaptic level and when this is required, electron microscopy is mandatory. FIB/SEM microscopy is a novel tool for three-dimensional high-resolution reconstructions, since it acquires automated serial images at ultrastructural level. Using FIB/SEM imaging, we observed, at 10 nm isotropic resolution, the same dendrites that were imaged in vivo over 9 days. Thus, we analyzed their ultrastructure and monitored the dynamics of the neuropil around them. We found that stable spines (present during the 9 days of imaging) formed typical asymmetric contacts with axons, whereas transient spines (present only during one day of imaging) did not form a synaptic contact. Our data suggest that the morphological classification that was assigned to a dendritic spine according to the in vivo images did not fit with its ultrastructural morphology. The correlative technique described herein is likely to open opportunities for unravelling the earlier unrecognized complexity of the nervous system.

Seamless stitching of tile scan microscope images.

Abstract: For diagnostic purposes, optical imaging techniques need to obtain high-resolution images of extended biological specimens in reasonable time. The field of view of an objective lens, however, is often smaller than the sample size. To image the whole sample, laser scanning microscopes acquire tile scans that are stitched into larger mosaics. The appearance of such image mosaics is affected by visible edge artefacts that arise from various optical aberrations which manifest in grey level jumps across tile boundaries. In this contribution, a technique for stitching tiles into a seamless mosaic is presented. The stitching algorithm operates by equilibrating neighbouring edges and forcing the brightness at corners to a common value. The corrected image mosaics appear to be free from stitching artefacts and are, therefore, suited for further image analysis procedures. The contribution presents a novel method to seamlessly stitch tiles captured by a laser scanning microscope into a large mosaic. The motivation for the work is the failure of currently existing methods for stitching nonlinear, multimodal images captured by our microscopic setups. Our method eliminates the visible edge artefacts that appear between neighbouring tiles by taking into account the overall illumination differences among tiles in such mosaics. The algorithm first corrects the nonuniform brightness that exists within each of the tiles. It then compensates for grey level differences across tile boundaries by equilibrating neighbouring edges and forcing the brightness at the corners to a common value. After these artefacts have been removed further image analysis procedures can be applied on the microscopic images. Even though the solution presented here is tailored for the aforementioned specific case, it could be easily adapted to other contexts where image tiles are assembled into mosaics such as in astronomical or satellite photos.

Empirical gradient threshold technique for automated segmentation across image modalities and cell lines.

Abstract: Summary New microscopy technologies are enabling image acquisition of terabyte-sized data sets consisting of hundreds of thousands of images. In order to retrieve and analyze the biological information in these large data sets, segmentation is needed to detect the regions containing cells or cell colonies. Our work with hundreds of large images (each 21 000×21 000 pixels) requires a segmentation method that: (1) yields high segmentation accuracy, (2) is applicable to multiple cell lines with various densities of cells and cell colonies, and several imaging modalities, (3) can process large data sets in a timely manner, (4) has a low memory footprint and (5) has a small number of user-set parameters that do not require adjustment during the segmentation of large image sets. None of the currently available segmentation methods meet all these requirements. Segmentation based on image gradient thresholding is fast and has a low memory footprint. However, existing techniques that automate the selection of the gradient image threshold do not work across image modalities, multiple cell lines, and a wide range of foreground/background densities (requirement 2) and all failed the requirement for robust parameters that do not require re-adjustment with time (requirement 5). We present a novel and empirically derived image gradient threshold selection method for separating foreground and background pixels in an image that meets all the requirements listed above. We quantify the difference between our approach and existing ones in terms of accuracy, execution speed, memory usage and number of adjustable parameters on a reference data set. This reference data set consists of 501 validation images with manually determined segmentations and image sizes ranging from 0.36 Megapixels to 850 Megapixels. It includes four different cell lines and two image modalities: phase contrast and fluorescent. Our new technique, called Empirical Gradient Threshold (EGT), is derived from this reference data set with a 10-fold cross-validation method. EGT segments cells or colonies with resulting Dice accuracy index measurements above 0.92 for all cross-validation data sets. EGT results has also been visually verified on a much larger data set that includes bright field and Differential Interference Contrast (DIC) images, 16 cell lines and 61 time-sequence data sets, for a total of 17 479 images. This method is implemented as an open-source plugin to ImageJ as well as a standalone executable that can be downloaded from the following link: https://isg.nist.gov/.

Correction of image drift and distortion in a scanning electron microscopy

Abstract: Continuous research on small-scale mechanical structures and systems has attracted strong demand for ultrafine deformation and strain measurements. Conventional optical microscope cannot meet such requirements owing to its lower spatial resolution. Therefore, high-resolution scanning electron microscope has become the preferred system for high spatial resolution imaging and measurements. However, scanning electron microscope usually is contaminated by distortion and drift aberrations which cause serious errors to precise imaging and measurements of tiny structures. This paper develops a new method to correct drift and distortion aberrations of scanning electron microscope images, and evaluates the effect of correction by comparing corrected images with scanning electron microscope image of a standard sample. The drift correction is based on the interpolation scheme, where a series of images are captured at one location of the sample and perform image correlation between the first image and the consequent images to interpolate the drift-time relationship of scanning electron microscope images. The distortion correction employs the axial symmetry model of charged particle imaging theory to two images sharing with the same location of one object under different imaging fields of view. The difference apart from rigid displacement between the mentioned two images will give distortion parameters. Three-order precision is considered in the model and experiment shows that one pixel maximum correction is obtained for the employed high-resolution electron microscopic system.

Sample holder for axial rotation of specimens in 3D microscopy

Abstract: Summary In common light microscopy, observation of samples is only possible from one perspective. However, especially for larger three-dimensionalspecimensobservationfromdifferentviews is desirable. Therefore, we are presenting a sample holder permitting rotation of the specimen around an axis perpendicular to the light path of the microscope. Thus, images can be

Detection of wood cell wall porosity using small carbohydrate molecules and confocal fluorescence microscopy

Abstract: A novel approach to nanoscale detection of cell wall porosity using confocal fluorescence microscopy is described. Infiltration of cell walls with a range of nitrophenyl-substituted carbohydrates of different molecular weights was assessed by measuring changes in the intensity of lignin fluorescence, in response to the quenching effect of the 4-nitrophenyl group. The following carbohydrates were used in order of increasing molecular weight; 4-nitrophenyl β-D-glucopyrano-side (monosaccharide), 4-nitrophenyl β-D-lactopyranoside (disaccharide), 2-chloro-4-nitrophenyl β-D-maltotrioside (trisaccharide), and 4-nitrophenyl α-D-maltopentaoside (pentasaccharide). This technique was used to compare cell wall porosity in wood which had been dewatered to 40% moisture content using supercritical CO2, where cell walls remain fully hydrated, with kiln dried wood equilibrated to 12% moisture content. Infiltration of cell walls as measured by fluorescence quenching, was found to decrease with increasing molecular weight, with the pentasaccharide being significantly excluded compared to the monosaccharide. Porosity experiments were performed on blocks and sections to assess differences in cell wall accessibility. Dewatered and kiln dried wood infiltrated as blocks showed similar results, but greater infiltration was achieved by using sections, indicating that not all pores were easily accessible by infiltration from the lumen surface. In wood blocks infiltrated with 4-nitrophenyl α-D-maltopentaoside, quenching of the secondary wall was quite variable, especially in kiln dried wood, indicating limited connectivity of pores accessible from the lumen surface.

Analysis of traction-free assumption in high-resolution EBSD measurements.

Abstract: The effects of using a traction-free (plane-stress) assumption to obtain the full distortion tensor from high-resolution EBSD measurements are analyzed. Equations are derived which bound the traction-free error arising from angular misorientation of the sample surface; the error in recovered distortion is shown to be quadratic with respect to that misorientation, and the maximum 'safe' angular misorientation is shown to be 2.7 degrees. The effects of localized stress fields on the traction-free assumption are then examined by a numerical case study, which uses the Boussinesq formalism to model stress fields near a free surface. Except in cases where localized stress field sources occur very close to sample points, the traction-free assumption appears to be admirably robust.

Performance evaluation of image segmentation algorithms on microscopic image data.

Abstract: Summary In our paper, we present a performance evaluation of image segmentation algorithms on microscopic image data. In spite of the existence of many algorithms for image data partitioning,thereisnouniversaland‘thebest’methodyet.Moreover, images of microscopic samples can be of various character and quality which can negatively influence the performance of image segmentation algorithms. Thus, the issue of selecting suitable method for a given set of image data is of big interest. We carried out a large number of experiments with a variety of segmentation methods to evaluate the behaviour of individual approaches on the testing set of microscopic images (cross-section images taken in three different modalitiesfromthefieldofartrestoration).Thesegmentationresults were assessed by several indices used for measuring the output quality of image segmentation algorithms. In the end, the benefit of segmentation combination approach is studied and applicability of achieved results on another representatives of microscopic data category ‐ biological samples ‐ is shown.

Metallothionein as a clonable tag for protein localization by electron microscopy of cells

Abstract: A benign, clonable tag for the localization of proteins by electron microscopy of cells would be valuable, especially if it provided labelling with high signal-to-noise ratio and good spatial resolution. Here we explore the use of metallothionein as such a localization marker. We have achieved good success with desmin labelled in vitro and with a component of the yeast spindle pole body labelled in cells. Heavy metals added after fixation and embedding or during the process of freeze-substitution fixation provide readily visible signals with no concern that the heavy atoms are affecting the behaviour of the protein in its physiological environment. However, our methods did not work with protein components of the nuclear pore complex, suggesting that this approach is not yet universally applicable. We provide a full description of our optimal labelling conditions and other conditions tried, hoping that our work will allow others to label their own proteins of interest and/or improve on the methods we have defined.

Automated image analysis of nuclear atypia in high-power field histopathological image.

Abstract: Summary Aims We developed a computer-aided technique to study nuclear atypia classification in high-power field haematoxylin and eosin stained images. Methods and results An automated technique for nuclear atypia score (NAS) calculation is proposed. The proposed technique uses sophisticated digital image analysis and machine-learning methods to measure the NAS for haematoxylin and eosin stained images. The proposed technique first segments all nuclei regions. A set of morphology and texture features is extracted from presegmented nuclei regions. The histogram of each feature is then calculated to characterize the statistical information of the nuclei. Finally, a support vector machine classifier is applied to classify a high-power field image into different nuclear atypia classes. A set of 1188 digital images was analysed in the experiment. We successfully differentiated the high-power field image with NAS1 versus non-NAS1, NAS2 versus non-NAS2 and NAS3 versus non-NAS3, with area under receiver-operating characteristic curve of 0.90, 0.86 and 0.87, respectively. In three classes evaluation, the average classification accuracy was 78.79%. We found that texture-based feature provides best performance for the classification. Conclusion The automated technique is able to quantify statistical features that may be difficult to be measured by human and demonstrates the future potentials of automated image analysis technique in histopathology analysis. Lay description The aim of this study is to develop a novel computer-aided framework to study nuclear atypia classification in high-power field haematoxylin and eosin stained images. Our study offered a novel technique to automatically analyse the nuclei atypia degree in digital image. The automated technique proposed to utilize high-lever statistical information that may be difficult to be measured by human and is able to provide good nuclear atypia classification performance. It showed great potential to be used as an adjunct in assisting diagnosis by pathologists in the future.

Quantitative comparison of segmentation algorithms for FIB-SEM images of porous media.

Abstract: Focused ion beam tomography has proven to be capable of imaging porous structures on a nano-scale. However, due to shine-through artefacts, common segmentation algorithms often lead to severe dislocation of individual structures in z-direction. Recently, a number of approaches have been developed, which take into account the specific nature of focused ion beam-scanning electron microscope images for porous media. In the present study, we analyse three of these approaches by comparing their performance based on simulated focused ion beam-scanning electron microscope images. Performance is measured by determining the amount of misclassified voxels as well as the fidelity of structural characteristics. Based on this analysis we conclude that each algorithm has certain strengths and weaknesses and we determine the scenarios for which each approach might be the best choice.

Microscopy of nanoparticulate dispersions

Abstract: We present a critical review of the common methods for determining the dispersion state of nanoparticulate samples particularly in liquid media, including the determination of particle size and morphology; particle size distributions and polydispersity and equilibrium particle structure and chemistry. We highlight the potential contributions of both scanning probe and electron microscopies in this analysis which is of benefit in understanding nanoparticulate formulations and their behaviour applied across a very wide range of technologies and industry sectors.

Phosphorus detection in vitrified bacteria by cryo-STEM annular dark-field analysis.

Abstract: Summary Bacterial cells often contain dense granules. Among these, polyphosphate bodies (PPBs) store inorganic phosphate for a variety of essential functions. Identification of PPBs has until now been accomplished by analytical methods that required drying or chemically fixing the cells. These methods entail large electron doses that are incompatible with low-dose imaging of cryogenic specimens. We show here that Scanning Transmission Electron Microscopy (STEM) of fully hydrated, intact, vitrified bacteria provides a simple means for mapping of phosphorus-containing dense granules based on quantitative sensitivity of the electron scattering to atomic number. A coarse resolution of the scattering angles distinguishes phosphorus from the abundant lighter atoms: carbon, nitrogen and oxygen. The theoretical basis is similar to Z contrast of materials science. EDX provides a positive identification of phosphorus, but importantly, the method need not involve a more severe electron dose than that required for imaging. The approach should prove useful in general for mapping of heavy elements in cryopreserved specimens when the element identity is known from the biological context. Lay description Biological cells consist primarily of the light elements: hydrogen, carbon, nitrogen, and oxygen. Heavier elements are also present in smaller quantities, e.g., calcium, magnesium, phosphorous, and iron. In certain contexts these may accumulate in specific cellular bodies or granules. While imaging in the electron microscope reveals the morphology, analytical tools are required in order to determine the elemental composition. These tools put severe constraints on sample preservation and are generally incompatible with cryogenically fixed specimens due to excessive irradiation by the electron beam. In this work we analyze phosphate-rich granules in intact, cryogenically-fixed bacteria using scanning transmission electron microscopy (STEM). Focused electrons are scattered to a range of angles that depends on the elements present locally in the specimen. We present both a theoretical basis to configure the microscope for elemental sensitivity and the experimental demonstration. In principle this analytical mapping entails the same electron radiation exposure as that required to form the image. The approach will be generally applicable for mapping of elements whose identity is known from the biological context.

Quantitative FRET measurement using emission‐spectral unmixing with independent excitation crosstalk correction

Abstract: Quantification of fluorescence resonance energy transfer (FRET) needs at least two external samples, an acceptor-only reference and a linked FRET reference, to calibrate fluorescence signal. Furthermore, all measurements for references and FRET samples must be performed under the same instrumental conditions. Based on a novel notion to predetermine the molar extinction coefficient ratio (RC ) of acceptor-to-donor for the correction of acceptor excitation crosstalk, we present here a robust and independent emission-spectral unmixing FRET methodology, Iem-spFRET, which can simultaneously measure the E and RC of FRET sample without any external references, such that Iem-spFRET circumvents the rigorous restriction of keeping the same imaging conditions for all FRET experiments and thus can be used for the direct measurement of FRET sample. We validate Iem-spFRET by measuring the absolute E and RC values of standard constructs with different acceptor-to-donor stoichiometry expressed in living cells. Our results demonstrate that Iem-spFRET is a simple and powerful tool for real-time monitoring the dynamic intermolecular interaction within single living cells.

Calcium silicate cement-induced remineralisation of totally demineralised dentine in comparison with glass ionomer cement: tetracycline labelling and two-photon fluorescence microscopy

Abstract: Two-photon fluorescence microscopy, in combination with tetracycline labelling, was used to observe the remineralising potentials of a calcium silicate-based restorative material (Biodentine(TM) ) and a glass ionomer cement (GIC:​Fuji​IX) on totally demineralised dentine. Forty demineralised dentine discs were stored with either cement in three different solutions: phosphate buffered saline (PBS) with tetracycline, phosphate-free tetracycline, and tetracycline-free PBS. Additional samples of demineralised dentine were stored alone in the first solution. After 8-week storage at 37 °C, dentine samples were imaged using two-photon fluorescence microscopy and Raman spectroscopy. Samples were later embedded in PMMA and polished block surfaces studied by 20 kV BSE imaging in an SEM to study variations in mineral concentration. The highest fluorescence intensity was exhibited by the dentine stored with Biodentine(TM) in the PBS/tetracycline solution. These samples also showed microscopic features of matrix remineralisation including a mineralisation front and intra- and intertubular mineralisation. In the other solutions, dentine exhibited much weaker fluorescence with none of these features detectable. Raman spectra confirmed the formation of calcium phosphate mineral with Raman peaks similar to apatite, while no mineral formation was detected in the dentine stored in cement-free or PBS-free media, or with GIC. It could therefore be concluded that Biodentine(TM) induced calcium phosphate mineral formation within the dentine matrix when stored in phosphate-rich media, which was selectively detectable using the tetracycline labelling.

Segmentation of elemental EDS maps by means of multiple clustering combined with phase identification

Abstract: An imaging concept is proposed for the phase identification and segmentation of elemental map images from energy dispersive spectroscopy. The procedure starts with presegmentation using common clustering algorithms, continues with automated identification of the chemical compositions, followed by their screening by professional expertise. The ultimate phases are finally clustered by applying a minimum Euclidean distance classifier. The potential, performance and limitations of the approach are presented on energy dispersive spectroscopy maps acquired by a scanning electron microscope and conducted on samples produced from cement clinker, natural rock and hydrated cement mortar. Nevertheless, the technique is suitable for arbitrary types of materials and general devices for energy dispersive spectroscopy acquisition. It is an approach for extending common energy dispersive spectroscopy analysis by means of visual examination and ratio plots towards quantitative rating.

A series of flexible design adaptations to the Nikon E-C1 and E-C2 confocal microscope systems for UV, multiphoton and FLIM imaging.

Abstract: Multiphoton microscopy is widely employed in the life sciences using extrinsic fluorescence of low- and high-molecular weight labels with excitation and emission spectra in the visible and near infrared regions. For imaging of intrinsic and extrinsic fluorophores with excitation spectra in the ultraviolet region, multiphoton excitation with one- or two-colour lasers avoids the need for ultraviolet-transmitting excitation optics and has advantages in terms of optical penetration in the sample and reduced phototoxicity. Excitation and detection of ultraviolet emission around 300 nm and below in a typical inverted confocal microscope is more difficult and requires the use of expensive quartz optics including the objective. In this technical note we describe the adaptation of a commercial confocal microscope (Nikon, Japan E-C1 or E-C2) for versatile use with Ti-sapphire and OPO laser sources and the addition of a second detection channel that enables detection of ultraviolet fluorescence and increases detection sensitivity in a typical fluorescence lifetime imaging microscopy experiment. Results from some experiments with this setup illustrate the resulting capabilities.

A simple but precise method for quantitative measurement of the quality of the laser focus in a scanning optical microscope

Abstract: We report a method for characterizing the focussing laser beam exiting the objective in a laser scanning microscope. This method provides the size of the optical focus, the divergence of the beam, the ellipticity and the astigmatism. We use a microscopic-scale knife-edge in the form of a simple transmission electron microscopy (TEM) grid attached to a glass microscope slide, and a light-collecting optical fibre and photodiode underneath the specimen. By scanning the laser spot from a reflective to a transmitting part of the grid, a beam profile in the form of an error function can be obtained and by repeating this with the knife-edge at different axial positions relative to the beam waist, the divergence and astigmatism of the post-objective laser beam can be obtained. The measured divergence can be used to quantify how much of the full numerical aperture of the lens is used in practice. We present data of the beam radius, beam divergence, ellipticity, and astigmatism obtained with low (0.15, 0.7) and high (1.3) numerical aperture lenses and lasers commonly used in confocal and multi-photon laser scanning microscopy. Our knife-edge method has several advantages over alternative knife-edge methods used in microscopy including that the knifeedge is easy to prepare, that the beam can be characterized also directly under a coverslip, as necessary to reduce spherical aberrations for objectives designed to be used with a coverslip, and it is suitable for use with commercial laser scanning microscopes where access to the laser beam can be limited.

Modelling mesoporous alumina microstructure with 3D random models of platelets

Abstract: This work focuses on a mesoporous material made of nanometric alumina "platelets" of unknown shape. We develop a 3D random microstructure to model the porous material , based on 2D Transmission Electron Microscopy (TEM) images, without prior knowledge on the spatial distribution of alumina inside the material. The TEM images , acquired on samples with thickness 300 nm, a scale much larger than the platelets's size, are too blurry and noisy to allow one to distinguish platelets or platelets aggregates individually. In a first step, the TEM images correlation function and integral range are estimated. The presence of long-range fluctuations, due to the TEM inhomogeneous detection , is detected and corrected by filtering. The corrected correlation function is used as a morphological descriptor for the model. After testing a Boolean model of platelets, a two-scales model of microstructure is introduced to replicate the statistical dispersion of platelets observed on TEM images. Accordingly a set of two-scales Boolean models with varying physically-admissible platelets shapes is proposed. Upon optimization, the model takes into account the dispersion of platelets in the microstructure as observed on TEM images. Comparing it to X-ray diffraction and nitrogen porosimetry data, the model is found to be in good agreement with the material in terms of specific surface area.

Exploration of the two‐photon excitation spectrum of fluorescent dyes at wavelengths below the range of the Ti:Sapphire laser

Abstract: We have studied the wavelength dependence of the two-photon excitation efficiency for a number of common UV excitable fluorescent dyes; the nuclear stains DAPI, Hoechst and SYTOX Green, chitin- and cellulose-staining dye Calcofluor White and Alexa Fluor 350, in the visible and near-infrared wavelength range (540–800 nm). For several of the dyes, we observe a substantial increase in the fluorescence emission intensity for shorter excitation wavelengths than the 680 nm which is the shortest wavelength usually available for two-photon microscopy. We also find that although the rate of photo-bleaching increases at shorter wavelengths, it is still possible to acquire many images with higher fluorescence intensity. This is particularly useful for applications where the aim is to image the structure, rather than monitoring changes in emission intensity over extended periods of time. We measure the excitation spectrum when the dyes are used to stain biological specimens to get a more accurate representation of the spectrum of the dye in a cell environment as compared to solution-based measurements.

Three-dimensional morphological modelling of concrete using multiscale Poisson polyhedra

Abstract: This paper aims at developing a random morphological model for concrete microstructures. A 3D image of concrete is obtained by microtomography and is used in conjunction with the concrete formulation to build and validate the model through morphological measurements. The morphological model is made up of two phases, corresponding to the matrix, or cement paste and to the aggregates. The set of aggregates in the sample is modelled as a combination of Poisson polyhedra of different scales. An algorithm is introduced to generate polyhedra packings in the continuum space. The latter is validated with morphological measurements.