scholarly journals Interactive web analysis and presentation of computercontrolled scanning electron microscopy data

1969 ◽  
Vol 20 ◽  
pp. 103-106
Author(s):  
Peter Riisager ◽  
Nynke Keulen ◽  
Uffe Larsen ◽  
Roger K. McLimans ◽  
Christian Knudsen ◽  
...  

In the following we describe the result of the Titan Project, an interactive web application (Titan) developed at the Geological Survey of Denmark and Greenland (GEUS) together with DuPont Titanium Technologies. The main aim of Titan is to make computer-controlled scanning electron microscopy (CCSEM) data, generated at GEUS, available via the internet. In brief, CCSEM is a method automatically to detect particles with a scanning electron microscope (SEM), and based on computer-controlled imagery to measure the chemistry and grain morphology of each particle in a given sample (Knudsen et al. 2005; Bernstein et al. 2008); Keulen et al. 2008. Titan makes data available on-line so that the user can interact with the data sets and analyse them using a web browser. In addition to CCSEM data, Titan contains a global database of titanium deposits and various reports. The web application is customised, such that the functionality and amount of data available for a given user depend on the privileges of that user.

2014 ◽  
Vol 1040 ◽  
pp. 230-235
Author(s):  
Pavlo Maruschak ◽  
Sergey Panin ◽  
Ilya Vlasov ◽  
Iryna Danyliuk ◽  
Roman Bishchak

Using the scanning electron microscopy data the main regularities of the fatigue crack propagation in the 17Mn1Si steel were studied. Based on fracture surface observation and analysis one can testify that the transition of the leading role of deformation and failure from the lower structural level to the higher one has the ordered pattern.


2017 ◽  
Author(s):  
E. Cocks ◽  
M. Taggart ◽  
F.C. Rind ◽  
K. White

AbstractSerial block face scanning electron microscopy (SBF-SEM) is a relatively new technique that allows the acquisition of serially sectioned, imaged and digitally aligned ultrastructural data. There is a wealth of information that can be obtained from the resulting image stacks but this presents a new challenge for researchers - how to computationally analyse and make best use of the large data sets produced. One approach is to reconstruct structures and features of interest in 3D. However the software programs can appear overwhelming, time consuming and not intuitive for those new to image analysis. There are a limited number of published articles that provide sufficient detail on how to do this type of reconstruction. Therefore the aim of this paper is to provide a detailed step-by-step protocol, videos and explanation on the types of analysis and programs that can be used. To showcase the programs, skeletal muscle from fetal and adult guinea pigs were used. The tissue was processed using the heavy metal protocol developed specifically for SBFSEM. Trimmed resin blocks were placed into a Zeiss Sigma SEM incorporating the Gatan 3View and the resulting image stacks were analysed in 3 different programs, Fiji, Amira and MIB, using a range of tools available for segmentation. The results from the image analysis comparison show that the analysis tools are often more suited to a type of structure. For example larger structures, such as nuclei and cells, can be segmented using interpolation, which speeds up analysis; single contrast structures, such as the nucleolus, can be segmented using the contrast-based thresholding tools. Knowing the nature of the tissue and its specific structures (complexity, contrast, if there are distinct membranes, size) will help to determine the best method for reconstruction and thus maximising output from valuable tissue.


2019 ◽  
Vol 19 (S6) ◽  
Author(s):  
Afshin Khadangi ◽  
Eric Hanssen ◽  
Vijay Rajagopal

Abstract Background With the advent of new high-throughput electron microscopy techniques such as serial block-face scanning electron microscopy (SBF-SEM) and focused ion-beam scanning electron microscopy (FIB-SEM) biomedical scientists can study sub-cellular structural mechanisms of heart disease at high resolution and high volume. Among several key components that determine healthy contractile function in cardiomyocytes are Z-disks or Z-lines, which are located at the lateral borders of the sarcomere, the fundamental unit of striated muscle. Z-disks play the important role of anchoring contractile proteins within the cell that make the heartbeat. Changes to their organization can affect the force with which the cardiomyocyte contracts and may also affect signaling pathways that regulate cardiomyocyte health and function. Compared to other components in the cell, such as mitochondria, Z-disks appear as very thin linear structures in microscopy data with limited difference in contrast to the remaining components of the cell. Methods In this paper, we propose to generate a 3D model of Z-disks within single adult cardiac cells from an automated segmentation of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The proposed fully automated segmentation scheme is comprised of three main modules including “pre-processing”, “segmentation” and “refinement”. We represent a simple, yet effective model to perform segmentation and refinement steps. Contrast stretching, and Gaussian kernels are used to pre-process the dataset, and well-known “Sobel operators” are used in the segmentation module. Results We have validated our model by comparing segmentation results with ground-truth annotated Z-disks in terms of pixel-wise accuracy. The results show that our model correctly detects Z-disks with 90.56% accuracy. We also compare and contrast the accuracy of the proposed algorithm in segmenting a FIB-SEM dataset against the accuracy of segmentations from a machine learning program called Ilastik and discuss the advantages and disadvantages that these two approaches have. Conclusions Our validation results demonstrate the robustness and reliability of our algorithm and model both in terms of validation metrics and in terms of a comparison with a 3D visualisation of Z-disks obtained using immunofluorescence based confocal imaging.


2020 ◽  
Vol 7 (4) ◽  
pp. 154-158
Author(s):  
E. V. Maraeva ◽  
N. V. Permiakov ◽  
Y. Y. Kedruk ◽  
L. V. Gritsenko ◽  
Kh. A. Abdullin

The work is devoted to the creation of a virtual device (computer program) for processing the results of sorption analysis of nanomaterials, including for estimating the size of nanoparticles based on the specific surface area. The obtained evaluation results were compared with the scanning electron microscopy data. Photocatalytically active zinc oxide samples were chosen as the object of the study.


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