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Deep-learning-based deformable image registration of head CT and MRI scans

Overview of attention for article published in Frontiers in Physics, December 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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1 X user

Readers on

mendeley
2 Mendeley
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Title
Deep-learning-based deformable image registration of head CT and MRI scans
Published in
Frontiers in Physics, December 2023
DOI 10.3389/fphy.2023.1292437
Authors

Alexander Ratke, Elena Darsht, Feline Heinzelmann, Kevin Kröninger, Beate Timmermann, Christian Bäumer

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 50%
Unknown 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Unknown 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 05 December 2023.
All research outputs
#21,219,867
of 26,061,338 outputs
Outputs from Frontiers in Physics
#1,338
of 4,543 outputs
Outputs of similar age
#264,054
of 374,403 outputs
Outputs of similar age from Frontiers in Physics
#26
of 138 outputs
Altmetric has tracked 26,061,338 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,543 research outputs from this source. They receive a mean Attention Score of 2.5. This one has gotten more attention than average, scoring higher than 56% 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 374,403 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.