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An improved level set method for vertebra CT image segmentation

Overview of attention for article published in BioMedical Engineering OnLine, May 2013
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1 X user
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1 Facebook page

Citations

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65 Dimensions

Readers on

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68 Mendeley
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Title
An improved level set method for vertebra CT image segmentation
Published in
BioMedical Engineering OnLine, May 2013
DOI 10.1186/1475-925x-12-48
Pubmed ID
Authors

Juying Huang, Fengzeng Jian, Hao Wu, Haiyun Li

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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Unknown 66 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 22%
Student > Master 14 21%
Student > Bachelor 11 16%
Researcher 7 10%
Student > Doctoral Student 3 4%
Other 7 10%
Unknown 11 16%
Readers by discipline Count As %
Engineering 24 35%
Medicine and Dentistry 13 19%
Computer Science 9 13%
Chemical Engineering 1 1%
Psychology 1 1%
Other 6 9%
Unknown 14 21%
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 29 May 2013.
All research outputs
#17,689,426
of 22,711,242 outputs
Outputs from BioMedical Engineering OnLine
#529
of 821 outputs
Outputs of similar age
#139,458
of 195,012 outputs
Outputs of similar age from BioMedical Engineering OnLine
#10
of 14 outputs
Altmetric has tracked 22,711,242 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 821 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 195,012 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.