scholarly journals Use of Negative Bias Potential for High Throughput Array Tomography in an Integrated Light-Electron Microscope

2019 ◽  
Vol 25 (S2) ◽  
pp. 1050-1051
Author(s):  
Ryan Lane ◽  
Yoram Vos ◽  
Pascal de Boer ◽  
Ben N.G. Giepmans ◽  
Jacob P. Hoogenboom
2021 ◽  
Vol 27 (S1) ◽  
pp. 1634-1636
Author(s):  
Akihiro Oosaki ◽  
Naoki Hosogi ◽  
Fumiaki Makino ◽  
Sohei Motoki ◽  
Isamu Ishikawa ◽  
...  

2013 ◽  
Vol 19 (S2) ◽  
pp. 1312-1313
Author(s):  
A. Hyde ◽  
J. Goulden ◽  
N. Rowlands ◽  
S. Ubhi

Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.


2020 ◽  
Author(s):  
Ryan Lane ◽  
Yoram Vos ◽  
Anouk H. G. Wolters ◽  
Luc van Kessel ◽  
Ben N.G. Giepmans ◽  
...  

AbstractLarge-scale electron microscopy (EM) allows analysis of both tissues and macromolecules in a semi-automated manner, but acquisition rate forms a bottleneck. We reasoned that a negative bias potential may be used to enhance signal collection, allowing shorter dwell times and thus increasing imaging speed. Negative bias potential has previously been used to tune penetration depth in block-face imaging. However, optimization of negative bias potential for application in thin section imaging will be needed prior to routine use and application in large-scale EM. Here, we present negative bias potential optimized through a combination of simulations and empirical measurements. We find that the use of a negative bias potential generally results in improvement of image quality and signal-to-noise ratio (SNR). The extent of these improvements depends on the presence and strength of a magnetic immersion field. Maintaining other imaging conditions and aiming for the same image quality and SNR, the use of a negative stage bias can allow for a 20-fold decrease in dwell time, thus reducing the time for a week long acquisition to less than 8 hours. We further show that negative bias potential can be applied in an integrated correlative light electron microscopy (CLEM) application, allowing fast acquisition of a high precision overlaid LM-EM dataset. Application of negative stage bias potential will thus help to solve the current bottleneck of image acquisition of large fields of view at high resolution in large-scale microscopy.


2021 ◽  
Author(s):  
Gayathri Mahalingam ◽  
Russel Torres ◽  
Daniel Kapner ◽  
Eric T Trautman ◽  
Tim Fliss ◽  
...  

Serial section Electron Microscopy can produce high throughput imaging of large biological specimen volumes. The high-resolution images are necessary to reconstruct dense neural wiring diagrams in the brain, so called connectomes. A high fidelity volume assembly is required to correctly reconstruct neural anatomy and synaptic connections. It involves seamless 2D stitching of the images within a serial section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP(Assembly Stitching and Alignment Pipeline) that is scalable and parallelized to work with distributed systems. The pipeline is built on top of the Render [18] services used in the volume assembly of the brain of adult Drosophila melanogaster [2]. It achieves high throughput by operating on the meta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. The modularity of ASAP allows for easy adaptation to new algorithms without significant changes to the workflow. The software pipeline includes a complete set of tools to do stitching, automated quality control, 3D section alignment, and rendering of the assembled volume to disk. We also implemented a workflow engine that executes the volume assembly workflow in an automated fashion triggered following the transfer of raw data. ASAP has been successfully utilized for continuous processing of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex [1, 25]. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.


2020 ◽  
Vol 26 (S2) ◽  
pp. 430-433
Author(s):  
Shuaishuai Sun ◽  
Xiaoyi Sun ◽  
Joseph Williams ◽  
Chong-Yu Ruan

2019 ◽  
Vol 25 (S2) ◽  
pp. 1038-1039
Author(s):  
Ryan Lane ◽  
Pascal de Boer ◽  
Ben N.G. Giepmans ◽  
Jacob P. Hoogenboom

2015 ◽  
Vol 259 (2) ◽  
pp. 114-120 ◽  
Author(s):  
A.L. EBERLE ◽  
S. MIKULA ◽  
R. SCHALEK ◽  
J. LICHTMAN ◽  
M.L. KNOTHE TATE ◽  
...  

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