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X Demographics
Mendeley readers
Attention Score in Context
| Title |
moco: Fast Motion Correction for Calcium Imaging
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, February 2016
|
| DOI | 10.3389/fninf.2016.00006 |
| Pubmed ID | |
| Authors |
Alexander Dubbs, James Guevara, Rafael Yuste |
| Abstract |
Motion correction is the first step in a pipeline of algorithms to analyze calcium imaging videos and extract biologically relevant information, for example the network structure of the neurons therein. Fast motion correction is especially critical for closed-loop activity triggered stimulation experiments, where accurate detection and targeting of specific cells in necessary. We introduce a novel motion-correction algorithm which uses a Fourier-transform approach, and a combination of judicious downsampling and the accelerated computation of many L 2 norms using dynamic programming and two-dimensional, fft-accelerated convolutions, to enhance its efficiency. Its accuracy is comparable to that of established community-used algorithms, and it is more stable to large translational motions. It is programmed in Java and is compatible with ImageJ. |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 20% |
| Mexico | 1 | 7% |
| Japan | 1 | 7% |
| Sweden | 1 | 7% |
| United Kingdom | 1 | 7% |
| Switzerland | 1 | 7% |
| Germany | 1 | 7% |
| San Marino | 1 | 7% |
| Unknown | 5 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 93% |
| Scientists | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 2% |
| Japan | 2 | 1% |
| France | 1 | <1% |
| Unknown | 165 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 58 | 34% |
| Researcher | 34 | 20% |
| Student > Master | 18 | 10% |
| Student > Postgraduate | 9 | 5% |
| Student > Bachelor | 7 | 4% |
| Other | 19 | 11% |
| Unknown | 27 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 52 | 30% |
| Agricultural and Biological Sciences | 42 | 24% |
| Engineering | 12 | 7% |
| Physics and Astronomy | 8 | 5% |
| Medicine and Dentistry | 8 | 5% |
| Other | 16 | 9% |
| Unknown | 34 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 13 May 2016.
All research outputs
#1,967,083
of 23,924,883 outputs
Outputs from Frontiers in Neuroinformatics
#68
of 783 outputs
Outputs of similar age
#32,117
of 301,006 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#2
of 13 outputs
Altmetric has tracked 23,924,883 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 783 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 91% 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 301,006 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 89% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.