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Automatic pulmonary fissure detection and lobe segmentation in CT chest images

Overview of attention for article published in BioMedical Engineering OnLine, January 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
51 Mendeley
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Title
Automatic pulmonary fissure detection and lobe segmentation in CT chest images
Published in
BioMedical Engineering OnLine, January 2014
DOI 10.1186/1475-925x-13-59
Pubmed ID
Authors

Shouliang Qi, Han J W van Triest, Yong Yue, Mingjie Xu, Yan Kang

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 2%
United Kingdom 1 2%
Portugal 1 2%
China 1 2%
Unknown 47 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 22%
Student > Master 11 22%
Researcher 6 12%
Student > Bachelor 3 6%
Other 2 4%
Other 5 10%
Unknown 13 25%
Readers by discipline Count As %
Engineering 13 25%
Medicine and Dentistry 8 16%
Computer Science 7 14%
Physics and Astronomy 4 8%
Agricultural and Biological Sciences 2 4%
Other 3 6%
Unknown 14 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 30 October 2019.
All research outputs
#3,179,423
of 16,109,489 outputs
Outputs from BioMedical Engineering OnLine
#91
of 666 outputs
Outputs of similar age
#92,411
of 368,985 outputs
Outputs of similar age from BioMedical Engineering OnLine
#1
of 1 outputs
Altmetric has tracked 16,109,489 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 666 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 85% 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 368,985 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them