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Fast parallel image registration on CPU and GPU for diagnostic classification of Alzheimer's disease

Overview of attention for article published in Frontiers in Neuroinformatics, January 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
2 blogs
twitter
1 X user
wikipedia
1 Wikipedia page

Citations

dimensions_citation
527 Dimensions

Readers on

mendeley
450 Mendeley
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Title
Fast parallel image registration on CPU and GPU for diagnostic classification of Alzheimer's disease
Published in
Frontiers in Neuroinformatics, January 2013
DOI 10.3389/fninf.2013.00050
Pubmed ID
Authors

Denis P. Shamonin, Esther E. Bron, Boudewijn P. F. Lelieveldt, Marion Smits, Stefan Klein, Marius Staring, for the Alzheimer's Disease Neuroimaging Initiative

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 450 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 <1%
France 3 <1%
United Kingdom 2 <1%
Netherlands 1 <1%
Brazil 1 <1%
South Africa 1 <1%
Denmark 1 <1%
Spain 1 <1%
United States 1 <1%
Other 0 0%
Unknown 435 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 119 26%
Student > Master 76 17%
Researcher 63 14%
Student > Bachelor 45 10%
Student > Postgraduate 19 4%
Other 57 13%
Unknown 71 16%
Readers by discipline Count As %
Engineering 93 21%
Medicine and Dentistry 66 15%
Computer Science 65 14%
Physics and Astronomy 35 8%
Agricultural and Biological Sciences 25 6%
Other 67 15%
Unknown 99 22%
Attention Score in Context

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 02 November 2023.
All research outputs
#2,228,306
of 25,837,817 outputs
Outputs from Frontiers in Neuroinformatics
#69
of 847 outputs
Outputs of similar age
#20,631
of 292,453 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#6
of 36 outputs
Altmetric has tracked 25,837,817 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 847 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. 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 292,453 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.