The Scanning Electron Microscope (SEM) as 2D imaging instrument has been widely used in biology and material sciences to determine the surface attributes of microscopic specimens. However the SEM micrographs still remain 2D images. To effectively measure and visualize the surface properties, we need to restore the shape model from the SEM images. Having 3D surfaces from SEM images would provide true anatomic shape of microscopic objects which allow for quantitative measurements and informative visualization of the system being investigated.The 3D Microscopy Dataset which is provided here includes both 2D images and 3D reconstructed surfaces of several biological material samples. To get the data and know about "Term Of Usage", please visit http://selibcv.org/3dsem/

Scanning electron microscopy (SEM) has an important application in the petroleum field, which is often used to analyze the microstructure of reservoir rocks, etc. Most of these analyses are based on two-dimensional images. In fact, SEM can carry out micro-nano scale three-dimensional measurement, and three-dimensional models can provide more accurate information than two-dimensional images. Among the commonly used SEM 3D reconstruction methods, parallax depth mapping is the most commonly used method. Multiple SEM images can be obtained by continuously tilting the sample table at a certain Angle, and multiple point clouds can be generated according to the parallax depth mapping method, and a more complete point clouds recovery can be achieved by combining the point clouds registration. However, the root mean square error of the point clouds generated by this method is relatively large and unstable after participating in point clouds registration. Therefore, this paper proposes a new method for generating point clouds. Firstly, the sample stage is rotated by a certain angle to obtain two SEM images. This operation makes the rotation matrix a known quantity. Then, based on the imaging model, an equation system is constructed to estimate the unknown translation parameters, and finally, triangulation is used to obtain the point clouds. The method proposed in this paper was tested on a publicly available 3D SEM image set, and the results showed that compared to the disparity depth mapping method, the point clouds generated by our method showed a significant reduction in root mean square error and relative rotation error in point clouds registration.

This dataset contains the raw volume electron microscopy (VEM) data used for the experiments presented in Figure 2 and Figure 3 of our manuscript, "Breaking Free from the Acquisition Dogma for Volume Electron Microscopy". The data supports our findings on supervised and self-supervised denoising strategies for accelerating VEM acquisition. All data was acquired from a mouse brain tissue sample using a Serial Block-Face Scanning Electron Microscope (SBF-SEM). XY pixel size for all tiff stacks is 15 nm.

This repository is organized into two main parts corresponding to the figures in the paper:

1. Supervised Denoising

SBEM2-Z50-fast.tif: A 3D TIFF stack of the snapshot stack. This volume was acquired with 0.5us pixel dwell time and a 50 nm section thickness.

SBEM2-Z50-slow.tif: A 3D TIFF stack of the reference stack. This volume was acquired with 2us pixel dwell time and a 50 nm section thickness.

2. Self-Supervised Denoising on Ultra-Thin Sections

SBEM3-Z20-300.tif, SBEM3-Z25-300.tif, SBEM3-Z50-300.tif: 3D TIFF stacks with acquired with 20 nm, 25nm and 50nm section thickness, respectively. Each stack contains about 300 slices. These stacks serves as the input for our self-supervised denoising model.

3D ultrastructure of myelinated and unmyelinated axons in a rat pelvic nerve visualized by serial block-face scanning electron microscopy (SBF-SEM)

A single Nickel nanowire has been characterised using 3 experimental techniques.Scanning electron microscope (SEM) data folder contains a single .TIFF image of a fallen Nickel nanowire, where the title refers to the name of the sample.Atomic and magnetic force micrscope (AFM and MFM) data folder contains raw output data where titles refer to the name of the sample (181017JA) and the magnetic field applied (eg 0mT), from software Nanoscope 5, these can be opened in any AFM processing software such as Gwyddion or WSxM. Each file contains data regarding the height (corresponding to AFM) and the phase (corresponding to the MFM).Simulation data folder contains .VTS files where the titles correspond to the appropriate field applied to the simulated wire. The file type .VTS can be opened and viewed within a 3D visualisation program such as Paraview. Research results based upon these data are published at https://doi.org/10.3390/nano10030429

The Cryo-Focused Ion Beam Scanning Electron Microscope (Cryo-FIB-SEM) market is experiencing robust growth, driven by advancements in cryo-electron microscopy (cryo-EM) and the increasing need for high-resolution 3D imaging in diverse scientific fields. The market, estimated at $250 million in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $800 million by 2033. This expansion is fueled by the capabilities of Cryo-FIB-SEM to visualize and analyze intricate cellular structures and macromolecular complexes at unprecedented detail, particularly crucial in structural biology, materials science, and nanotechnology. Key drivers include the rising demand for advanced imaging techniques in drug discovery, the growing adoption of cryo-EM in academic research, and the continuous technological improvements in instrument sensitivity and automation. Leading players like JEOL, Carl Zeiss, and Thermo Fisher Scientific are at the forefront of innovation, driving market competition and pushing the boundaries of resolution and imaging speed. However, the market faces certain restraints. The high cost of Cryo-FIB-SEM systems limits accessibility, primarily for smaller research institutions and laboratories. Furthermore, the specialized expertise required for operation and data analysis presents a barrier to entry. Nevertheless, the increasing availability of grants and funding for advanced research, along with the development of user-friendly software and streamlined workflows, is gradually mitigating these challenges. Market segmentation reveals a strong presence in North America and Europe, reflecting the concentration of leading research institutions and high technological adoption rates in these regions. The ongoing development of correlative microscopy techniques, integrating Cryo-FIB-SEM with other imaging modalities, promises to further enhance its applications and market potential, accelerating growth in the coming years.

We used Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) to perform a 3D analysis of the synapses in the layer III neuropils of the Brodmann areas 3b (somatosensory), 4 (motor), and 17 (visual primary) from human brain samples. 3 human brain autopsies cases have been used to achieve a total of 22 FIB/SEM valid image stacks: 4 stacks in BA17 from a single case (AB7); 9 stacks in BA3b (three stacks per case, AB2, AB3, and AB7); and 9 stacks in BA4 (three stacks per case, AB2, AB3, and AB7). Specifically, we studied synaptic junctions, which were fully reconstructed in 3D. We analyzed the synaptic density, 3D spatial distribution, and type (excitatory and inhibitory), as well as the shape and size of each synaptic junction. Moreover, their postsynaptic targets were determined. The present dataset constitutes a detailed description of the synaptic characteristics of the human cortex, which is a necessary step to better understand the organization of the cortex.

Focused ion beam (FIB) tomography is a destructive technique used to collect three-dimensional (3D) structural information at a resolution of a few nanometers. For FIB tomography, a material sample is degraded by layer-wise milling. After each layer, the current surface is imaged by a scanning electron microscope (SEM), providing a consecutive series of cross-sections of the three-dimensional material sample. Especially for nanoporous materials, the reconstruction of the 3D microstructure of the material, from the information collected during FIB tomography, is impaired by the so-called shine-through effect. This effect prevents a unique mapping between voxel intensity values and material phase (e.g., solid or void). It often substantially reduces the accuracy of conventional methods for image segmentation. Here we demonstrate how machine learning can be used to tackle this problem. A bottleneck in doing so is the availability of sufficient training data. To overcome this problem, we present a novel approach to generate synthetic training data in the form of FIB-SEM images generated by Monte Carlo simulations. Based on this approach, we compare the performance of different machine learning architectures for segmenting FIB tomography data of nanoporous materials. We demonstrate that two-dimensional (2D) convolutional neural network (CNN) architectures processing a group of adjacent slices as input data as well as 3D CNN perform best and can enhance the segmentation performance significantly.

The Focused Ion Beam Scanning Electron Microscope (FIB-SEM) market is experiencing steady growth, projected to reach a value of $1638.9 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 4.2% from 2025 to 2033. This growth is fueled by increasing demand across diverse sectors, including semiconductor manufacturing, materials science research, and life sciences. Advancements in FIB-SEM technology, such as improved resolution, faster imaging speeds, and enhanced automation, are key drivers. The ability to perform high-precision 3D imaging and micro-fabrication makes FIB-SEMs indispensable for applications requiring detailed nanoscale analysis. The market is segmented by application (e.g., semiconductor failure analysis, materials characterization, biological sample imaging), and by geographic region, with North America and Europe currently dominating due to strong research infrastructure and a high concentration of leading companies such as Thermo Fisher Scientific, Hitachi High-Technologies Corporation, JEOL Ltd., Carl Zeiss, and Tescan Group. Competition is intense, with companies focusing on innovation and strategic partnerships to expand their market share. Despite the positive outlook, challenges remain. The high cost of FIB-SEM systems is a significant barrier to entry, particularly for smaller research institutions and companies in developing economies. Furthermore, the need for specialized expertise to operate and maintain these complex instruments presents a limitation. However, ongoing technological advancements, alongside the increasing availability of financing options and service contracts, are expected to mitigate these restraints gradually. The market is expected to witness considerable innovation in areas such as automation, higher throughput, and user-friendly software, leading to wider adoption and accessibility. The increasing adoption of advanced analytical techniques combined with the growing need for higher resolution imaging will contribute to the market's expansion.

Dataset of raw and image processed 3D Cryo-FIB SEM data recorded from Mallomonas cells.

3D x-ray tomography and 2D scanning electron microscopy (SEM) data behind the publications:

Salling FB, Jeppesen N, Sonne MR, Hattel JH and Mikkelsen LP. Individual fibre inclination segmentation from X-ray computed tomography using principal component analysis. Composites Part A, Submitted

to where the reference should be given if used.

Details on the data-set is given in the Data-in-Brief publications:

Salling FB, Hattel JH, Mikkelsen LP. X-ray computed tomography and scanning electron microscopy datasets of unidirectional and textured glass fibre composites. Data in Brief, Submitted

The data-files is given for the two material case called Mock and UD. For each material case, the data is given as:

• .txm-files: 3D reconstructed x-ray scan files
  • FoV 2mm binning 2 (analyzed in the paper)
  • FoV 4mm binning 1 (additional data-set)
• 2Dtif.zip-files: 2D tif-stack version of the 3D reconstructed data-set
• .tif-files: stitched SEM scanning file used for fiber volume fraction determination
• .hdr-files: meta-data ASCII file behind the SEM scan
• tif.zip-files: The individual images behind the stitched SEM scanning file
• fig-files: digital form of the fibre trajectories colored according to their individual mean inclination used in figure xx in reference yy
• m-files: Matlab-script for calculating the fibre volume fraction (Vf) from the SEM image
• mat-files: Mat-file with the segmented part in the SEM image used for the Vf calculation

The data are in the proprietary dm4 format as saved by the acquisition software. However, they can be easily opened and converted in Fiji/ImageJ with the Bioformats importer. We recommend alignment of the stack and binning of 2x2 for working with the data.

The global Focused Ion Beam Scanning Electron Microscope (FIB-SEM) system market is experiencing robust growth, projected to reach $578.3 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.5% from 2025 to 2033. This expansion is driven by several key factors. Advancements in semiconductor technology necessitate higher resolution imaging and precise material modification at the nanoscale, fueling demand for FIB-SEM systems in research and development. The increasing adoption of FIB-SEM in life sciences, particularly for 3D cellular imaging and analysis, further contributes to market growth. Material science applications, such as failure analysis and characterization of new materials, also represent a significant market segment. The market is segmented by ion source type (Ga Ion Source and Non-Ga Ion Source) and application (Material Science, Life Sciences, and Semiconductor). Leading players like Thermo Fisher Scientific, Hitachi, Zeiss, JEOL Ltd, Tescan Group, and Raith are driving innovation and competition within this dynamic market. Geographical distribution reveals a strong presence across North America, Europe, and Asia Pacific, reflecting the concentration of research institutions and advanced manufacturing facilities in these regions. Growth in emerging markets, such as those in Asia Pacific and the Middle East & Africa, is anticipated to be significant in the coming years, driven by increasing investment in scientific research and technological advancement. While the market faces some restraints, such as the high cost of FIB-SEM systems and the need for specialized expertise for operation and maintenance, the overall growth trajectory remains positive, propelled by continuous technological innovations and the expanding applications of FIB-SEM across various scientific disciplines. The market is expected to see significant growth across all segments with the semiconductor industry and life sciences expected to be the most prominent growth drivers in the coming years.

The brain contains thousands of millions of synapses, exhibiting diverse structural, molecular, and functional characteristics. However, synapses can be classified into two primary morphological types: Gray’s type I and type II, corresponding to Colonnier’s asymmetric (AS) and symmetric (SS) synapses, respectively. AS and SS have a thick and thin postsynaptic density, respectively. In the cerebral cortex, since most AS are excitatory (glutamatergic), and SS are inhibitory (GABAergic), determining the distribution, size, density, and proportion of the two major cortical types of synapses is critical, not only to better understand synaptic organization in terms of connectivity, but also from a functional perspective. However, several technical challenges complicate the study of synapses. Potassium ferrocyanide has been utilized in recent volume electron microscope studies to enhance electron density in cellular membranes. However, identifying synaptic junctions, especially SS, becomes more challenging as the postsynaptic densities become thinner with increasing concentrations of potassium ferrocyanide. Here we describe a protocol employing Focused Ion Beam Milling and Scanning Electron Microscopy for studying brain tissue. The focus is on the unequivocal identification of AS and SS types. To validate SS observed using this protocol as GABAergic, experiments with immunocytochemistry for the vesicular GABA transporter were conducted on fixed mouse brain tissue sections. This material was processed with different concentrations of potassium ferrocyanide, aiming to determine its optimal concentration. We demonstrate that using a low concentration of potassium ferrocyanide (0.1%) improves membrane visualization while allowing unequivocal identification of synapses as AS or SS.

The dataset consists of scanning electron microscope (SEM) images of 3D-imprinted microneedles from fabricated conductive, UV-cured hydrogels composites Financing: Miniatura 7, DEC-2023/07/X/ST5/01377.

In this project I work on developing ways to use a FIB-SEM to create a 3D model of biological samples. The method can be used in several projects with Grøn Dyst angles and I here report on my work on imaging malaria infected blood cells which is essential for a deeper understanding of how the parasite might be targeted by medicine, and algae samples that are essential for ecotoxicologial studies and later will be used for algae species used in biomass and biofuel production.

The global Scanning Electron Microscope (SEM) market, valued at $3.718 billion in 2025, is projected to experience robust growth, driven by increasing demand across diverse sectors. The compound annual growth rate (CAGR) of 4.5% from 2025 to 2033 indicates a significant expansion, fueled primarily by advancements in SEM technology, leading to enhanced resolution, faster imaging speeds, and broader applications. Key drivers include the rising adoption of SEMs in life sciences for detailed cellular and sub-cellular analysis, material sciences for characterizing material properties at the nanoscale, and semiconductor industries for quality control and defect analysis. The increasing prevalence of nanotechnology research and development further fuels market growth. Furthermore, the continuous innovation in FIB-SEM technology, offering 3D imaging capabilities, expands the scope of applications across various research and industrial domains. Competition among leading manufacturers like Thermo Fisher Scientific, Hitachi High-Technologies Corporation, and Jeol Ltd. drives technological advancements and market expansion. Segmentation by application (Life Sciences, Material Sciences) and type (W-SEM, FEG-SEM, FIB-SEM) highlights distinct growth trajectories, with the FIB-SEM segment expected to witness faster expansion owing to its superior capabilities. Regional variations in market growth are anticipated, with North America and Asia Pacific (particularly China) expected to dominate the market due to high research spending and technological adoption. However, challenges such as high initial investment costs and the need for skilled personnel could potentially restrain market growth to some extent. The forecast period from 2025 to 2033 anticipates substantial market expansion based on the projected CAGR and ongoing technological developments. Continued miniaturization and improved sensitivity of SEMs are anticipated to further broaden their applications in fields like medical diagnostics, environmental monitoring, and forensic science. The integration of advanced analytical techniques with SEMs, such as energy-dispersive X-ray spectroscopy (EDS), will also contribute to market growth. Despite potential challenges, the overall market outlook for SEMs remains highly positive, driven by the intrinsic value of detailed nanoscale imaging across numerous scientific and industrial applications. Growth is expected across all regions, with particular strength in established markets and emerging economies showing increasing investment in research and development.

Research data that supports the findings presented in the manuscript "Stochastic 3D modeling of nanostructured NVP/C active material particles for sodium-ion batteries" published in Batteries & Supercaps (https://doi.org/10.1002/batt.202300409).

This includes

1) Experimental image data obtained by focused ion beam scanning electron microscopy (FIB-SEM), high-resolution SEM (HR-SEM), transmission electron microscopy (TEM), and enery-dispersive X-ray spectoscropy (EDX). Imaging is described in Section 2.3.

2) Segmented image data of FIB-SEM stack and HR-SEM images, which build the basis for calibrating the stochastic model in Section 3.2. The segmentation has been performed as described in Section 2.4.

3) Virtual nanostructures generated by the stochastic model in order to study structure-property relationships in Section 4.2.

Serial block-face (SBF) scanning electron microscopy (SEM) is used for imaging the entire internal ultrastructure of cells, tissue samples or small organisms. We developed a workflow for SBF SEM of adherent cells, such as Giardia parasites and HeLa cells, attached to the surface of a plastic culture dish, which preserves the interface between cells and plastic substrate. Cells were embedded in situ on their substrate using silicone microwells and were mounted for cross-sectioning which allowed SBF imaging of large volumes and many cells. In total we provide 10 data sets with image series from SBF SEM of Giardia and HeLa cells prepared with protocol variants to improve the workflow. A detailed description of the methods and the data set is provided in the download container.

Data set 03 comprises an image 3D model of a Giardia lamblia cell adhered to the plastic substrate of a culture dish. The model was generated by segmentation of the entire cell, the cell nuclei (red) and the ventral disc cytoskeleton (yellow) in an image series of 276 images which was recorded by SBF SEM (see dataset 01). Section interval was 50 nm and pixel size 10 nm. The data folder contains the model-file (Imaris-format) and a 360° rotation of the model as video file (mp4-format).