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Quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images

Overview of attention for article published in BMC Medical Imaging, August 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#18 of 450)
  • High Attention Score compared to outputs of the same age (84th percentile)

Mentioned by

twitter
1 tweeter
patent
3 patents
peer_reviews
1 peer review site
facebook
1 Facebook page

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
24 Mendeley
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Title
Quantitative evaluation of an automatic segmentation method for 3D reconstruction of intervertebral scoliotic disks from MR images
Published in
BMC Medical Imaging, August 2012
DOI 10.1186/1471-2342-12-26
Pubmed ID
Authors

Chevrefils Claudia, Cheriet Farida, Grimard Guy, Miron Marie-Claude, Aubin Carl-Eric

Abstract

For some scoliotic patients the spinal instrumentation is inevitable. Among these patients, those with stiff curvature will need thoracoscopic disk resection. The removal of the intervertebral disk with only thoracoscopic images is a tedious and challenging task for the surgeon. With computer aided surgery and 3D visualisation of the interverterbral disk during surgery, surgeons will have access to additional information such as the remaining disk tissue or the distance of surgical tools from critical anatomical structures like the aorta or spinal canal. We hypothesized that automatically extracting 3D information of the intervertebral disk from MR images would aid the surgeons to evaluate the remaining disk and would add a security factor to the patient during thoracoscopic disk resection.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 13%
Student > Bachelor 3 13%
Student > Doctoral Student 3 13%
Researcher 3 13%
Student > Master 3 13%
Other 6 25%
Unknown 3 13%
Readers by discipline Count As %
Medicine and Dentistry 8 33%
Nursing and Health Professions 3 13%
Computer Science 3 13%
Agricultural and Biological Sciences 1 4%
Psychology 1 4%
Other 3 13%
Unknown 5 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 25 August 2020.
All research outputs
#2,981,440
of 18,724,433 outputs
Outputs from BMC Medical Imaging
#18
of 450 outputs
Outputs of similar age
#21,047
of 137,969 outputs
Outputs of similar age from BMC Medical Imaging
#1
of 1 outputs
Altmetric has tracked 18,724,433 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 450 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done particularly well, scoring higher than 96% 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 137,969 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 84% 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