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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SBEMimage: Versatile Acquisition Control Software for Serial Block-Face Electron Microscopy
|
|---|---|
| Published in |
Frontiers in Neural Circuits, July 2018
|
| DOI | 10.3389/fncir.2018.00054 |
| Pubmed ID | |
| Authors |
Benjamin Titze, Christel Genoud, Rainer W. Friedrich |
| Abstract |
We present SBEMimage, an open-source Python-based application to operate serial block-face electron microscopy (SBEM) systems. SBEMimage is designed for complex, challenging acquisition tasks, such as large-scale volume imaging of neuronal tissue or other biological ultrastructure. Advanced monitoring, process control, and error handling capabilities improve reliability, speed, and quality of acquisitions. Debris detection, autofocus, real-time image inspection, and various other quality control features minimize the risk of data loss during long-term acquisitions. Adaptive tile selection allows for efficient imaging of large tissue volumes of arbitrary shape. The software's graphical user interface is optimized for remote operation. In its user-friendly viewport, tile grids covering the region of interest to be acquired are overlaid on previously acquired overview images of the sample surface. Images from other sources, e.g., light microscopes, can be imported and superimposed. SBEMimage complements existing DigitalMicrograph (Gatan Microscopy Suite) installations on 3View systems but permits higher acquisition rates by interacting directly with the microscope's control software. Its modular architecture and the use of Python/PyQt make SBEMimage highly customizable and extensible, which allows for fast prototyping and will permit adaptation to a wide range of SBEM systems and applications. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 14% |
| United States | 2 | 14% |
| Belgium | 1 | 7% |
| Switzerland | 1 | 7% |
| Unknown | 8 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 86% |
| Scientists | 1 | 7% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 28% |
| Student > Master | 6 | 15% |
| Student > Ph. D. Student | 4 | 10% |
| Student > Doctoral Student | 3 | 8% |
| Student > Bachelor | 3 | 8% |
| Other | 2 | 5% |
| Unknown | 11 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 25% |
| Neuroscience | 8 | 20% |
| Biochemistry, Genetics and Molecular Biology | 6 | 15% |
| Physics and Astronomy | 3 | 8% |
| Social Sciences | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 10 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 February 2021.
All research outputs
#4,078,594
of 23,098,660 outputs
Outputs from Frontiers in Neural Circuits
#252
of 1,222 outputs
Outputs of similar age
#78,673
of 329,833 outputs
Outputs of similar age from Frontiers in Neural Circuits
#5
of 29 outputs
Altmetric has tracked 23,098,660 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,222 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,833 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.