Ultrafast cell edge detection by line‐scan time‐stretch microscopy

Ultrafast time‐stretch imaging technique recently attracts an increasing interest for applications in cell classification due to high throughput and high sensitivity. A novel imaging modality of time‐stretch imaging technique for edge detection is proposed. Edge detection based on the directional derivative is realized using differential detection. As the image processing is mainly implemented in the physical layer, the computation complexity of edge extraction is significantly reduced. An imaging system for edge detection with the scan rate of 77.76 MHz is experimentally demonstrated. Resolution target is first measured to verify the feasibility of the edge extraction. Furthermore, various cells, including red blood cells, lung cancer cells and breast cancer cells, are detected. The edges of cancerous cells present in a completely different form. The imaging system for edge detection would be a good candidate for high‐throughput cell classification.      

Interpolated Compressed Sensing for 2D Multiple Slice Fast MR Imaging

Sparse MRI has been introduced to reduce the acquisition time and raw data size by undersampling the k-space data. However, the image quality, particularly the contrast to noise ratio (CNR), decreases with the undersampling rate. In this work, we proposed an interpolated Compressed Sensing (iCS) method to further enhance the imaging speed or reduce data size without significant sacrifice of image quality and CNR for multi-slice two-dimensional sparse MR imaging in humans. This method utilizes the k-space data of the neighboring slice in the multi-slice acquisition. The missing k-space data of a highly undersampled slice are estimated by using the raw data of its neighboring slice multiplied by a weighting function generated from low resolution full k-space reference images. In-vivo MR imaging in human feet has been used to investigate the feasibility and the performance of the proposed iCS method. The results show that by using the proposed iCS reconstruction method, the average image error can be reduced and the average CNR can be improved, compared with the conventional sparse MRI reconstruction at the same undersampling rate.     

Quantitative high-speed imaging of entire developing embryos with simultaneous multiview light-sheet microscopy

Live imaging of large biological specimens is fundamentally limited by the short optical penetration depth of light microscopes. To maximize physical coverage, we developed the SiMView technology framework for high-speed in vivo imaging, which records multiple views of the specimen simultaneously. SiMView consists of a light-sheet microscope with four synchronized optical arms, real-time electronics for long-term sCMOS-based image acquisition at 175 million voxels per second, and computational modules for high-throughput image registration, segmentation, tracking and real-time management of the terabytes of multiview data recorded per specimen. We developed one-photon and multiphoton SiMView implementations and recorded cellular dynamics in entire Drosophila melanogaster embryos with 30-s temporal resolution throughout development. We furthermore performed high-resolution long-term imaging of the developing nervous system and followed neuroblast cell lineages in vivo. SiMView data sets provide quantitative morphological information even for fast global processes and enable accurate automated cell tracking in the entire early embryo.     

Extended-resolution imaging of the interaction of lipid droplets and mitochondria

Physical contacts between organelles play a pivotal role in intracellular trafficking of metabolites. Monitoring organelle interactions in living cells using fluorescence microscopy is a powerful approach to functionally assess these cellular processes. However, detailed target acquisition is typically limited due to light diffraction. Furthermore, subcellular compartments such as lipid droplets and mitochondria are highly dynamic and show significant subcellular movement. Thus, high-speed acquisition of these organelles with extended-resolution is appreciated. Here, we present an imaging informatics pipeline enabling spatial and time-resolved analysis of the dynamics and interactions of fluorescently labeled lipid droplets and mitochondria in a fibroblast cell line. The imaging concept is based on multispectral confocal laser scanning microscopy and includes high-speed resonant scanning for fast spatial acquisition of organelles. Extended-resolution is achieved by the recording of images at minimized pinhole size and by post-processing of generated data using a computational image restoration method. Computation of inter-organelle contacts is performed on basis of segmented spatial image data. We show limitations of the image restoration and segmentation part of the imaging informatics pipeline. Since both image processing methods are implemented in other related methodologies, our findings will help to identify artifacts and the false-interpretation of obtained morphometric data. As a proof-of-principle, we studied how lipid load and overexpression of PLIN5, considered to be involved in the tethering of LDs and mitochondria, affects organelle association.     

Image-based screening: a technology in transition

Image-based screening (IBS) has proven itself with whole-well assays in which throughput and assay miniaturization are priorities. Recent interest, however, has centered upon the use of automated imaging technology to conduct assays at subcellular resolution. These in vitro assays have the potential to increase lead quality at early stages in drug discovery. Subcellular IBS is not yet mature and, although some assays provide reliable data at reasonable throughput, many others have yet to demonstrate robust application. Developments in image acquisition, analysis and informatics technologies are ongoing and are expected to broaden the usefulness of subcellular IBS.     

A high‐throughput all‐optical laser‐scanning imaging flow cytometer with biomolecular specificity and subcellular resolution

Image‐based cellular assay advances approaches to dissect complex cellular characteristics through direct visualization of cellular functional structures. However, available technologies face a common challenge, especially when it comes to the unmet need for unraveling population heterogeneity at single‐cell precision: higher imaging resolution (and thus content) comes at the expense of lower throughput, or vice versa. To overcome this challenge, a new type of imaging flow cytometer based upon an all‐optical ultrafast laser‐scanning imaging technique, called free‐space angular‐chirp‐enhanced delay (FACED) is reported. It enables an imaging throughput (>20 000 cells s^?1) 1 to 2 orders of magnitude higher than the camera‐based imaging flow cytometers. It also has 2 critical advantages over optical time‐stretch imaging flow cytometry, which achieves a similar throughput: (1) it is widely compatible to the repertoire of biochemical contrast agents, favoring biomolecular‐specific cellular assay and (2) it enables high‐throughput visualization of functional morphology of individual cells with subcellular resolution. These capabilities enable multiparametric single‐cell image analysis which reveals cellular heterogeneity, for example, in the cell‐death processes demonstrated in this work—the information generally masked in non‐imaging flow cytometry. Therefore, this platform empowers not only efficient large‐scale single‐cell measurements, but also detailed mechanistic analysis of complex cellular processes.      

Fast Keyhole MR Imaging Using Optimized k-Space Data Acquisition

In some dynamic magnetic resonance imaging (MRI) applications, the sample is still, and only the signal intensity changes with time. For such cases, the keyhole imaging principle can be used. In standard keyhole imaging, a low-frequency image signal is acquired, using a limited number of phase-encoding steps, which correspond to the rectangular sampling region in the k-space center. However, such a region practically never coincides with the position of the k-space points, which carry the most relevant low-frequency image information. In this paper we propose an improved keyhole method, which allows dynamic acquisition of a low-frequency image signal from selected most relevant k-space points via fast imaging mechanisms. Dynamic data acquisition is executed in the presence of time-varying magnetic-field (MF) gradients after single sample excitation. Special care has been taken in the design of the gradient sequence to minimize gradient load. This improved keyhole imaging method has been considered theoretically and verified experimentally on a model system.     

MITICS (MALDI Imaging Team Imaging Computing System): a new open source mass spectrometry imaging software

MITICS is a new software developed for MALDI imaging. We tried to render this software compatible with all types of instruments. MITICS is divided in two parts: MITICS control for data acquisition and MITICS Image for data processing and images reconstruction. MITICS control is available for Applied BioSystems MALDI-TOF instruments and MITICS Image for both Applied BioSystems and Bruker Daltonics ones. MITICS Control provides an interface to the user for setting the acquisition parameters for the imaging sequence, namely set instruments acquisition parameters, create the raster of acquisition and control post-acquisition data processing, and provide this settings to the automatic acquisition software of the MALDI instrument. MITICS Image ensures image reconstruction, files are first converted to XML files before being loaded in a database. In MITICS image we have chosen to implement different data representations and calculations for image reconstruction. MITICS Image uses three different representations that have shown to ease extraction of information from the whole data set. It also offers image reconstruction base either on the maximum peak intensity or the peak area. Image reconstruction is possible for single ions but also by summing signals of different ions. MITICS was validated on biological cases.     

Emerging technologies in mass spectrometry imaging

Mass spectrometry imaging (MSI) as an analytical tool for bio-molecular and bio-medical research targets accurate compound localization and identification. In terms of dedicated instrumentation, this translates into the demand for more detail in the image dimension (spatial resolution) and in the spectral dimension (mass resolution and accuracy), preferably combined in one instrument. At the same time, large area biological tissue samples require fast acquisition schemes, instrument automation and a robust data infrastructure. This review discusses the analytical capabilities of an "ideal" MSI instrument for bio-molecular and bio-medical molecular imaging. The analytical attributes of such an ideal system are contrasted with technological and methodological challenges in MSI. In particular, innovative instrumentation for high spatial resolution imaging in combination with high sample throughput is discussed. Detector technology that targets various shortcomings of conventional imaging detector systems is highlighted. The benefits of accurate mass analysis, high mass resolving power, additional separation strategies and multimodal three-dimensional data reconstruction algorithms are discussed to provide the reader with an insight in the current technological advances and the potential of MSI for bio-medical research.     

Auto-align - multi-modality fluorescence microscopy image co-registration

Multi-modality microscopes incorporate multiple microscopy techniques into one module, imaging through a common objective lens. Simultaneous or consecutive image acquisition of a single specimen, using multiple techniques, increases the amount of measurable information available. In order to benefit from each modality, it is necessary to accurately co-register data sets. Intrinsic differences in the image formation process employed by each modality result in images which possess different characteristics. In addition, as a result of using different measurement devices, images often differ in size and can suffer relative geometrical deformations including rotation, scale and translation, making registration a complex problem. Current methods generally rely on manual input and are therefore subject to human error. Here, we present an automated image registration tool for fluorescence microscopy. We show that it successfully registers images obtained via total internal reflection fluorescence (TIRF), or epi-fluorescence, and confocal microscopy. Furthermore, we provide several other applications including channel merging following image acquisition through an emission beam splitter, and lateral stage drift correction. We also discuss areas of membrane trafficking which could benefit from application of Auto-Align. Auto-Align is an essential item in the advanced microscopist's toolbox which can create a synergy of single or multi-modality image data.     

Ultraviolet imaging densitometry of unstained gels for two-dimensional electrophoresis

A system suitable for ultraviolet imaging densitometry of two-dimensional electrophoretic gels that are unstained is described, together with its applications. A flying-spot densitometer linked with a personal computer was used for data acquisition, generation of mapping data, and image processing. Randomly distributed zones of proteins on two-dimensional gels were detected at 280 nm without being stained by two-dimensional scanning, and the densitometric value of each pixel (0.2 x 0.2 mm) was memorized by the computer, which generated a mapping pattern with density contours. The amount and densitometric value of cytochrome c had a linear relationship in the range of 2-200 micrograms. Zone locations of bovine liver proteins separated on two-dimensional gels were indicated on a map expressed in X-Y coordinates, and the pIs and molecular weights could be calculated from the map by use of pI and molecular weight markers on the same gel.     

Continuous image and electrophysiological recording with real-time processing and control.

Collecting continuous video together with multichannel electrophysiological data and other experimental modalities requires high bandwidth and storage capacities, as well as accurate synchronization to detect correlations between different recorded events. Often, experiments are highly complex, with many variables requiring immediate analysis and feedback during the course of the experiment. In addition, output channels require real-time control with high time resolution. We have explored several approaches to a system that can perform the above functions. The design of our system considered a number of issues, including time intervals between control and acquisition events, longest continuous recording period, data transfer bottleneck considerations, file archiving and format, and real-time display and processing. To demonstrate the system, we describe an experiment for characterizing rapid evoked scattered light changes in neural tissue, in vivo, using simultaneous electronic image acquisition and electrophysiological recording.     

Development of automated imaging and analysis for zebrafish chemical screens.

We demonstrate the application of image-based high-content screening (HCS) methodology to identify small molecules that can modulate the FGF/RAS/MAPK pathway in zebrafish embryos. The zebrafish embryo is an ideal system for in vivo high-content chemical screens. The 1-day old embryo is approximately 1mm in diameter and can be easily arrayed into 96-well plates, a standard format for high throughput screening. During the first day of development, embryos are transparent with most of the major organs present, thus enabling visualization of tissue formation during embryogenesis. The complete automation of zebrafish chemical screens is still a challenge, however, particularly in the development of automated image acquisition and analysis. We previously generated a transgenic reporter line that expresses green fluorescent protein (GFP) under the control of FGF activity and demonstrated their utility in chemical screens ¹. To establish methodology for high throughput whole organism screens, we developed a system for automated imaging and analysis of zebrafish embryos at 24-48 hours post fertilization (hpf) in 96-well plates ². In this video we highlight the procedures for arraying transgenic embryos into multiwell plates at 24hpf and the addition of a small molecule (BCI) that hyperactivates FGF signaling ³. The plates are incubated for 6 hours followed by the addition of tricaine to anesthetize larvae prior to automated imaging on a Molecular Devices ImageXpress Ultra laser scanning confocal HCS reader. Images are processed by Definiens Developer software using a Cognition Network Technology algorithm that we developed to detect and quantify expression of GFP in the heads of transgenic embryos. In this example we highlight the ability of the algorithm to measure dose-dependent effects of BCI on GFP reporter gene expression in treated embryos.     

Adaptive Imaging Cytometry to Estimate Parameters of Gene Networks Models in Systems and Synthetic Biology

The use of microfluidics in live cell imaging allows the acquisition of dense time-series from individual cells that can be perturbed through computer-controlled changes of growth medium. Systems and synthetic biologists frequently perform gene expression studies that require changes in growth conditions to characterize the stability of switches, the transfer function of a genetic device, or the oscillations of gene networks. It is rarely possible to know a priori at what times the various changes should be made, and the success of the experiment is unknown until all of the image processing is completed well after the completion of the experiment. This results in wasted time and resources, due to the need to repeat the experiment to fine-tune the imaging parameters. To overcome this limitation, we have developed an adaptive imaging platform called GenoSIGHT that processes images as they are recorded, and uses the resulting data to make real-time adjustments to experimental conditions. We have validated this closed-loop control of the experiment using galactose-inducible expression of the yellow fluorescent protein Venus in Saccharomyces cerevisiae. We show that adaptive imaging improves the reproducibility of gene expression data resulting in more accurate estimates of gene network parameters while increasing productivity ten-fold.     

Lattice micropatterning for cryo-electron tomography studies of cell-cell contacts

Cryo-electron tomography is the highest resolution tool available for structural analysis of macromolecular complexes within their native cellular environments. At present, data acquisition suffers from low throughput, in part due to the low probability of positioning a cell such that the subcellular structure of interest is on a region of the electron microscopy (EM) grid that is suitable for imaging. Here, we photo-micropatterned EM grids to optimally position endothelial cells so as to enable high-throughput imaging of cell-cell contacts. Lattice micropatterned grids increased the average distance between intercellular contacts and thicker cell nuclei such that the regions of interest were sufficiently thin for direct imaging. We observed a diverse array of membranous and cytoskeletal structures at intercellular contacts, demonstrating the utility of this technique in enhancing the rate of data acquisition for cellular cryo-electron tomography studies.     

Accelerated Optical Projection Tomography Applied to In Vivo Imaging of Zebrafish

Optical projection tomography (OPT) provides a non-invasive 3-D imaging modality that can be applied to longitudinal studies of live disease models, including in zebrafish. Current limitations include the requirement of a minimum number of angular projections for reconstruction of reasonable OPT images using filtered back projection (FBP), which is typically several hundred, leading to acquisition times of several minutes. It is highly desirable to decrease the number of required angular projections to decrease both the total acquisition time and the light dose to the sample. This is particularly important to enable longitudinal studies, which involve measurements of the same fish at different time points. In this work, we demonstrate that the use of an iterative algorithm to reconstruct sparsely sampled OPT data sets can provide useful 3-D images with 50 or fewer projections, thereby significantly decreasing the minimum acquisition time and light dose while maintaining image quality. A transgenic zebrafish embryo with fluorescent labelling of the vasculature was imaged to acquire densely sampled (800 projections) and under-sampled data sets of transmitted and fluorescence projection images. The under-sampled OPT data sets were reconstructed using an iterative total variation-based image reconstruction algorithm and compared against FBP reconstructions of the densely sampled data sets. To illustrate the potential for quantitative analysis following rapid OPT data acquisition, a Hessian-based method was applied to automatically segment the reconstructed images to select the vasculature network. Results showed that 3-D images of the zebrafish embryo and its vasculature of sufficient visual quality for quantitative analysis can be reconstructed using the iterative algorithm from only 32 projections—achieving up to 28 times improvement in imaging speed and leading to total acquisition times of a few seconds.     

Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools

The vast amount of data produced by today’s medical imaging systems has led medical professionals to turn to novel technologies in order to efficiently handle their data and exploit the rich information present in them. In this context, artificial intelligence (AI) is emerging as one of the most prominent solutions, promising to revolutionise every day clinical practice and medical research. The pillar supporting the development of reliable and robust AI algorithms is the appropriate preparation of the medical images to be used by the AI-driven solutions. Here, we provide a comprehensive guide for the necessary steps to prepare medical images prior to developing or applying AI algorithms. The main steps involved in a typical medical image preparation pipeline include: (i) image acquisition at clinical sites, (ii) image de-identification to remove personal information and protect patient privacy, (iii) data curation to control for image and associated information quality, (iv) image storage, and (v) image annotation. There exists a plethora of open access tools to perform each of the aforementioned tasks and are hereby reviewed. Furthermore, we detail medical image repositories covering different organs and diseases. Such repositories are constantly increasing and enriched with the advent of big data. Lastly, we offer directions for future work in this rapidly evolving field.     

Multi‐ATOM: Ultrahigh‐throughput single‐cell quantitative phase imaging with subcellular resolution

A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost‐effective and label‐free cellular assays, which provides useful insights into understanding the biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single‐cell precision to define cell identities in a large and heterogeneous population of cells—hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multiplexed asymmetric‐detection time‐stretch optical microscopy (multi‐ATOM) that captures and processes quantitative label‐free single‐cell images at ultrahigh throughput without compromising subcellular resolution. We show that multi‐ATOM, based upon ultrafast phase‐gradient encoding, outperforms state‐of‐the‐art QPI in permitting robust phase retrieval at a QPI throughput of >10 000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi‐ATOM for large‐scale, label‐free, multivariate, cell‐type classification (e.g. breast cancer subtypes, and leukemic cells vs peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi‐ATOM could empower new strategies in large‐scale biophysical single‐cell analysis with applications in biology and enriching disease diagnostics.      

Light sheet microscopy for real-time developmental biology

Within only a few short years, light sheet microscopy has contributed substantially to the emerging field of real-time developmental biology. Low photo-toxicity and high-speed multiview acquisition have made selective plane illumination microscopy (SPIM) a popular choice for studies of organ morphogenesis and function in zebrafish, Drosophila, and other model organisms. A multitude of different light sheet microscopes have emerged for the noninvasive imaging of specimens ranging from single molecules to cells, tissues, and entire embryos. In particular, developmental biology can benefit from the ability to watch developmental events occur in real time in an entire embryo, thereby advancing our understanding on how cells form tissues and organs. However, it presents a new challenge to our existing data and image processing tools. This review gives an overview of where we stand as light sheet microscopy branches out, explores new areas, and becomes more specialized.