Multi-beam Scanning Electron Microscope Research Articles

Large-scale Connectomics with Multi-Beam Scanning Electron Microscopy

Large-scale Connectomics with Multi-Beam Scanning Electron Microscopy

Msemalign: a pipeline for serial section multibeam scanning electron microscopy volume alignment.

Serial section multibeam scanning electron microscopy (ssmSEM) is currently among the fastest technologies available for acquiring 3D anatomical data spanning relatively large neural tissue volumes, on the order of 1 mm3 or larger, at a resolution sufficient to resolve the fine detail of neuronal morphologies and synapses. These petabyte-scale volumes can be analyzed to create connectomes, datasets that contain detailed anatomical information including synaptic connectivity, neuronal morphologies and distributions of cellular organelles. The mSEM acquisition process creates hundreds of millions of individual image tiles for a single cubic-millimeter-sized dataset and these tiles must be aligned to create 3D volumes. Here we introduce msemalign, an alignment pipeline that strives for scalability and design simplicity. The pipeline can align petabyte-scale datasets such that they contain smooth transitions as the dataset is navigated in all directions, but critically that does so in a fashion that minimizes the overall magnitude of section distortions relative to the originally acquired micrographs.

In multi electron beam systems, “Neighbours Matter”

In the Multi beam source (MBS) of our Multi Beam Scanning Electron Microscope (MBSEM), an aperture lens array (ALA) splits the emission cone of the Schottky field emitter into multiple beamlets. When the apertures in the ALA are close to each other, the ALA can introduce aberrations to these beamlets through the electrostatic interaction of neighbouring apertures with each aperture's lens field. When the apertures are arranged in a square grid pattern, the aberration causes fourfold astigmatism. The effect on the beam spot is analyzed through a combination of 3D simulations and experimental validation. To counterbalance the fourfold astigmatism, a correction scheme is proposed in which a slightly non-round profile is applied to the aperture lenses.

Defect detection and classification on imec iN5 node BEoL test vehicle with multibeam scanning electron microscope

We present an automated application for defect detection and classification from ZEISS multibeam scanning electron microscope (MultiSEM®) images, based on machine learning (ML) technology. We acquire MultiSEM images of a semiconductor wafer suited for process window characterization at the imec iN5 logic node and use a dedicated application to train ML models for defect detection and classification. We show the user flow for training and execution, and the resulting capture and nuisance rates. Due to straightforward parallelization, the application is designed for the large amounts of data generated rapidly by the MultiSEM.

Characterization and Optimization of OSTEM; A Novel Detection Method for Single- and Multi-Beam Scanning Electron Microscopy

Characterization and Optimization of OSTEM; A Novel Detection Method for Single- and Multi-Beam Scanning Electron Microscopy

How innovations in methodology offer new prospects for volume electron microscopy

Detailed knowledge of biological structure has been key in understanding biology at several levels of organisation, from organs to cells and proteins. Volume electron microscopy (volume EM) provides high resolution 3D structural information about tissues on the nanometre scale. However, the throughput rate of conventional electron microscopes has limited the volume size and number of samples that can be imaged. Recent improvements in methodology are currently driving a revolution in volume EM, making possible the structural imaging of whole organs and small organisms. In turn, these recent developments in image acquisition have created or stressed bottlenecks in other parts of the pipeline, like sample preparation, image analysis and data management. While the progress in image analysis is stunning due to the advent of automatic segmentation and server‐based annotation tools, several challenges remain. Here we discuss recent trends in volume EM, emerging methods for increasing throughput and implications for sample preparation, image analysis and data management.

Development of Human Gut Organoids With Resident Tissue Macrophages as a Model of Intestinal Immune Responses.

Development of Human Gut Organoids With Resident Tissue Macrophages as a Model of Intestinal Immune Responses.

Connectomics of Bone to Brain-Probing Physical Renderings of Cellular Experience.

“Brainless” cells, the living constituents inhabiting all biological materials, exhibit remarkably smart, i.e., stimuli-responsive and adaptive, behavior. The emergent spatial and temporal patterns of adaptation, observed as changes in cellular connectivity and tissue remodeling by cells, underpin neuroplasticity, muscle memory, immunological imprinting, and sentience itself, in diverse physiological systems from brain to bone. Connectomics addresses the direct connectivity of cells and cells’ adaptation to dynamic environments through manufacture of extracellular matrix, forming tissues and architectures comprising interacting organs and systems of organisms. There is imperative to understand the physical renderings of cellular experience throughout life, from the time of emergence, to growth, adaptation and aging-associated degeneration of tissues. Here we address this need through development of technological approaches that incorporate cross length scale (nm to m) structural data, acquired via multibeam scanning electron microscopy, with machine learning and information transfer using network modeling approaches. This pilot case study uses cutting edge imaging methods for nano- to meso-scale study of cellular inhabitants within human hip tissue resected during the normal course of hip replacement surgery. We discuss the technical approach and workflow and identify the resulting opportunities as well as pitfalls to avoid, delineating a path for cellular connectomics studies in diverse tissue/organ environments and their interactions within organisms and across species. Finally, we discuss the implications of the outlined approach for neuromechanics and the control of physical behavior and neuromuscular training.

Double Cones and the Diverse Connectivity of Photoreceptors and Bipolar Cells in an Avian Retina.

Double cones are the most common photoreceptor cell type in most avian retinas, but their precise functions remain a mystery. Among their suggested functions are luminance detection, polarized light detection, and light-dependent, radical pair-based magnetoreception. To better understand the function of double cones, it will be crucial to know how they are connected to the neural network in the avian retina. Here we use serial sectioning, multibeam scanning electron microscopy to investigate double-cone anatomy and connectivity with a particular focus on their contacts to other photoreceptor and bipolar cells in the chicken retina. We found that double cones are highly connected to neighboring double cones and with other photoreceptor cells through telodendria-to-terminal and telodendria-to-telodendria contacts. We also identified 15 bipolar cell types based on their axonal stratifications, photoreceptor contact pattern, soma position, and dendritic and axonal field mosaics. Thirteen of these 15 bipolar cell types contacted at least one or both members of the double cone. All bipolar cells were bistratified or multistratified. We also identified surprising contacts between other cone types and between rods and cones. Our data indicate a much more complex connectivity network in the outer plexiform layer of the avian retina than originally expected.SIGNIFICANCE STATEMENT Like in humans, vision is one of the most important senses for birds. Here, we present the first serial section multibeam scanning electron microscopy dataset from any bird retina. We identified many previously undescribed rod-to-cone and cone-to-cone connections. Surprisingly, of the 15 bipolar cell types we identified, 11 received input from rods and 13 of 15 received at least part of their input from double cones. Therefore, double cones seem to play many different and important roles in avian retinal processing, and the neural network and thus information processing in the outer retina are much more complex than previously expected. These fundamental findings will be very important for several fields of science, including vertebrate vision, avian magnetoreception, and comparative neuroanatomy.

Transmission imaging on a scintillator in a scanning electron microscope

Large area electron microscopy (EM) imaging has long been difficult due to fundamental limits in throughput for conventional electron microscopes. New developments in transmission electron microscopy and multi-beam scanning electron microscopy (MBSEM) imaging have however made it possible to generate large EM datasets [1,2,3]. This article describes a transmission imaging technique that is suitable for a MBSEM as it allows for a relatively straightforward way of separating the signals generated by each beam. The technique places a thin (50nm-200nm) tissue section directly on top of a coated scintillator. The electrons that are transmitted through the section generate light in the scintillator which is collected by a high NA objective and imaged onto a photon detector. This article gives a model for the contrast-to-noise (CNR) and signal-to-noise (SNR) ratio that is to be expected for this imaging technique. These parameters were calculated using Monte-Carlo simulations. It was found that the CNR increases when decreasing landing energy and SNR increases with increasing landing energy. These two trends cause that there is an intermediate energy where imaging performance is best. The energy of this optimum was calculated for various levels of heavy metal staining, section thickness, coating material, coating thickness and light collection efficiency. The model was verified experimentally on a synthetic sample.

Gas cluster ion beam SEM for imaging of large tissue samples with 10 nm isotropic resolution

We demonstrate gas cluster ion beam scanning electron microscopy (SEM), in which wide-area ion milling is performed on a series of thick tissue sections. This three-dimensional electron microscopy technique acquires datasets with <10 nm isotropic resolution of each section, and these can then be stitched together to span the sectioned volume. Incorporating gas cluster ion beam SEM into existing single-beam and multibeam SEM workflows should be straightforward, increasing reliability while improving z resolution by a factor of three or more.

Development of standard samples with programmed defects for evaluation of pattern inspection tools for 7-nm and smaller nodes

Background: Continued shrinkage of pattern size has caused difficulties in detecting small defects. Multibeam scanning electron microscopy (SEM) is a potential method for pattern inspection below 7-nm node. Performance of the tool depends on charge control, resolution, and defect detection capability. Aim: The goal of this study is to develop a method for evaluating the performance of multibeam SEM for 7-nm nodes. Approach: By developing various standard samples with programmed defects (PDs) on 12 in. Si wafer, we evaluate the performance of multibeam SEM. Results: The first wafer had line and space (LS) patterns and PDs with varying contrast. A second wafer had various shaped small PDs, ∼5 nm in size in 16- to 12-nm half-pitch LS patterns. A third wafer with extremely small PDs of around 1 nm was fabricated in LS patterns with ultralow line-edge roughness (LER) of less than 1 nm. The first wafer was effective for charge control, whereas second and third wafer confirms resolution and defect detection capability. Conclusions: A set of minimum three standard wafer samples is effective to confirm the performance of multibeam SEM for below 7-nm nodes. Besides, we proposed a method to verify the LER values measured by a critical-dimension SEM.

Towards Fast and Direct Memory Read-out by Multi-beam Scanning Electron Microscopy and Deep Learning Image Classification

Journal Article Towards Fast and Direct Memory Read-out by Multi-beam Scanning Electron Microscopy and Deep Learning Image Classification Get access Kyle Crosby, Kyle Crosby Carl Zeiss Microscopy LLC, Business Development mSEM, One Zeiss Drive, Thornwood, USA Search for other works by this author on: Oxford Academic Google Scholar Tomasz Garbowski, Tomasz Garbowski Carl Zeiss Microscopy GmbH, Business Development mSEM, Oberkochen, Germany Search for other works by this author on: Oxford Academic Google Scholar Stephan Nickell Stephan Nickell Carl Zeiss Microscopy GmbH, Business Development mSEM, Oberkochen, Germany Corresponding author: Stephan.Nickell@Zeiss.com Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 25, Issue S2, 1 August 2019, Pages 192–193, https://doi.org/10.1017/S1431927619001697 Published: 01 August 2019

Shawn Mikula

In the summer of 2017, I contacted Shawn, then working at the Max Planck Institute in Martinsried, to ask him to join the Editorial Board of the Journal of Comparative Neurology (JCN). I was very impressed by his scientific acumen and his research on high-throughput electron microscopy that he wanted to apply at the level of an entire brain. Shawn immediately accepted and became a member of our journal's board in January 2018. Even before he was officially a member of the board, with characteristic enthusiasm, he began to assemble a group of contributors for a special issue of JCN dedicated to cutting-edge methods and approaches to structural and functional mapping of the mouse brain. Most unfortunately, his tenure as a member of JCN's board was to be a short one. With great sadness, we learned in July 2018 Shawn's tragic passing. We lost a great friend, a highly dedicated and dynamic colleague, and one of the most talented and promising young investigator in neuroscience at a point when he was developing his career independently at Keio University in Japan. Shawn's career was brief and cut short, but remarkably productive. He received his College Education at the University of Texas in Austin, where he graduated in 1998 with no fewer than three BS degrees in Mathematics, Physics, and Biochemistry. He then completed his PhD in neuroscience in 2005 at Johns Hopkins University School of Medicine at the Krieger Mind-Brain Institute in Baltimore, MD, under the mentorship of Ernst Niebur. Afterward, he was a postdoctoral researcher with Ted Jones at the University of California Davis where he developed the BrainMaps project, an internet-enabled multiresolution histochemical and tract-tracing brain atlas for various mammalian species. He moved on to Germany in 2009 for further postdoctoral work with Winfried Denk at the Max Planck Institute for Medical Research in Heidelberg, to pursue his work on comprehensive mapping the mammalian whole-brain circuitry and structure at the synaptic level using high-throughput volume electron microscopy. He became a Researcher at the Max Planck Institute for Neurobiology in Martinsried in 2013 where he developed methods to prepare small mammalian brains for electron microscopy and to image them using high-throughput multibeam scanning electron microscopy. In 2018, he moved to Japan, first at the National Institute for Physiological Sciences in Okazaki, and a few months later to Keio University School of Medicine in Tokyo, where he had just been appointed Assistant Professor at the time he passed away, working on a comprehensive ultrastructural mapping of the circuitry of the whole mouse brain at a single-synapse level of resolution. His goals were eventually to apply these approaches to small nonhuman primate brains. A list of Shawn's major scientific contributions appears at the end of this editorial. This special issue reflects Shawn's last efforts as an editor for our journal. It represents our recognition of his outstanding work and a memory of his contributions to understanding the mammalian whole-brain connectome and developing new techniques “to reconstruct the whole brain's wiring diagram.” The articles assembled in the present issue summarize recent efforts to attain a functional and structural connectome map of the mouse brain through multimodal and multiscale approaches. I am personally indebted to the many contributors who participated in the completion of this issue after Shawn's death and graciously helped me finalize it in a timely manner to celebrate the memory of our friend and colleague. We also express our most sincere and heartfelt condolences to his friends and family.

Large-Area Fluorescence and Electron Microscopic Correlative Imaging With Multibeam Scanning Electron Microscopy.

Recent improvements in correlative light and electron microscopy (CLEM) technology have led to dramatic improvements in the ability to observe tissues and cells. Fluorescence labeling has been used to visualize the localization of molecules of interest through immunostaining or genetic modification strategies for the identification of the molecular signatures of biological specimens. Newer technologies such as tissue clearing have expanded the field of observation available for fluorescence labeling; however, the area of correlative observation available for electron microscopy (EM) remains restricted. In this study, we developed a large-area CLEM imaging procedure to show specific molecular localization in large-scale EM sections of mouse and marmoset brain. Target molecules were labeled with antibodies and sequentially visualized in cryostat sections using fluorescence and gold particles. Fluorescence images were obtained by light microscopy immediately after antibody staining. Immunostained sections were postfixed for EM, and silver-enhanced sections were dehydrated in a graded ethanol series and embedded in resin. Ultrathin sections for EM were prepared from fully polymerized resin blocks, collected on silicon wafers, and observed by multibeam scanning electron microscopy (SEM). Multibeam SEM has made rapid, large-area observation at high resolution possible, paving the way for the analysis of detailed structures using the CLEM approach. Here, we describe detailed methods for large-area CLEM in various tissues of both rodents and primates.

Electron Microscopy Sample Preparation Protocol Enabling Nano-to-mesoscopic Mapping of Cellular Connectomes and Their Habitats in Human Tissues and Organs.

Multibeam scanning electron microscopy (multiSEM) provides a technical platform for seamless nano-to-mesoscale mapping of cells in human tissues and organs, which is a major new initiative of the U.S. National Institutes of Health. Such cross-length-scale imaging is expected to provide unprecedented understanding of relationships between cellular health and tissue-organ as well as organismal-scale health outcomes. For example, understanding relationships between loss in cell viability and cell network connectivity enables identification of emergent behaviors and prediction of degenerative disease onset, in organs as diverse as bone and brain, at early timepoints, providing a basis for future treatments and prevention. Developed for rapid throughput imaging of minute defects on semiconductor wafers, multiSEM has recently been adapted for imaging of human organs, their constituent tissues, and their respective cellular inhabitants. Through integration of geospatial approaches, statistical and network modelling, advances in computing and the management of immense datasets, as well as recent developments in machine learning that enable the automation of big data analyses, multiSEM and other cross- cutting imaging technologies have the potential to exert a profound impact on elucidation of disease mechanisms, translating to improvements in human health. Here we provide a protocol for acquisition and preparation of sample specimen sizes of diagnostic relevance for human anatomy and physiology. We discuss challenges and opportunities to integrate this approach with multibeam scanning electron microscopy workflows as well as multiple imaging modalities for mapping of organ and tissue structure and function.

Multi-Beam Scanning Electron Microscopy for High-Throughput Imaging in Connectomics Research.

Major progress has been achieved in recent years in three-dimensional microscopy techniques. This applies to the life sciences in general, but specifically the neuroscientific field has been a main driver for developments regarding volume imaging. In particular, scanning electron microscopy offers new insights into the organization of cells and tissues by volume imaging methods, such as serial section array tomography, serial block-face imaging or focused ion beam tomography. However, most of these techniques are restricted to relatively small tissue volumes due to the limited acquisition throughput of most standard imaging techniques. Recently, a novel multi-beam scanning electron microscope technology optimized to the imaging of large sample areas has been developed. Complemented by the commercialization of automated sample preparation robots, the mapping of larger, cubic millimeter range tissue volumes at high-resolution is now within reach. This Mini Review will provide a brief overview of the various approaches to electron microscopic volume imaging, with an emphasis on serial section array tomography and multi-beam scanning electron microscopic imaging.

High Throughput Shale Rock Imaging Using Multi-Beam Scanning Electron Microscopy

High Throughput Shale Rock Imaging Using Multi-Beam Scanning Electron Microscopy

Creating High-Resolution Multiscale Maps of Human Tissue Using Multi-beam SEM.

Multi-beam scanning electron microscopy (mSEM) enables high-throughput, nano-resolution imaging of macroscopic tissue samples, providing an unprecedented means for structure-function characterization of biological tissues and their cellular inhabitants, seamlessly across multiple length scales. Here we describe computational methods to reconstruct and navigate a multitude of high-resolution mSEM images of the human hip. We calculated cross-correlation shift vectors between overlapping images and used a mass-spring-damper model for optimal global registration. We utilized the Google Maps API to create an interactive map and provide open access to our reconstructed mSEM datasets to both the public and scientific communities via our website www.mechbio.org. The nano- to macro-scale map reveals the tissue’s biological and material constituents. Living inhabitants of the hip bone (e.g. osteocytes) are visible in their local extracellular matrix milieu (comprising collagen and mineral) and embedded in bone’s structural tissue architecture, i.e. the osteonal structures in which layers of mineralized tissue are organized in lamellae around a central blood vessel. Multi-beam SEM and our presented methodology enable an unprecedented, comprehensive understanding of health and disease from the molecular to organ length scale.

Transmission electron imaging in the Delft multibeam scanning electron microscope 1

Our group is developing a multibeam scanning electron microscope (SEM) with 196 beams in order to increase the throughput of SEM. Three imaging systems using, respectively, transmission electron detection, secondary electron detection, and backscatter electron detection are designed in order to make it as versatile as a single beam SEM. This paper focuses on the realization of the transmission electron imaging system, which is motivated by biologists' interest in the particular contrast this can give. A thin sample is placed on fluorescent material which converts the transmitted electrons to photons. Then, the 196 photon beams are focused with a large magnification onto a camera via a high quality optical microscope integrated inside the vacuum chamber. Intensities of the transmission beams are retrieved from the camera images and constructed to form each beam's image using an off line image processing program. Experimental results prove the working principle of transmission electron imaging and show that details of 10–20 nm in images of biological specimen are visible. Problems encountered in the results are discussed and plans for future improvements are suggested.