↓ Skip to main content

Application of a Semiautomated Contour Segmentation Tool to Identify the Intervertebral Nucleus Pulposus in MR Images

Overview of attention for article published in American Journal of Neuroradiology, June 2010
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

patent
14 patents

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
32 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Application of a Semiautomated Contour Segmentation Tool to Identify the Intervertebral Nucleus Pulposus in MR Images
Published in
American Journal of Neuroradiology, June 2010
DOI 10.3174/ajnr.a2162
Pubmed ID
Authors

B.P. Bechara, S.K. Leckie, B.W. Bowman, C.E. Davies, B.I. Woods, E. Kanal, G.A. Sowa, J.D. Kang

Abstract

Accurate identification of the NP in MR images is crucial to properly and objectively assess the intervertebral disk. Therefore, computerized segmentation of the NP in T2WI is necessary to produce repeatable and accurate results with minimal user input. A semiautomated CS method was developed to identify the NP in T2WI on the basis of intensity differences compared with the AF. The method was validated by segmenting computer-generated images with a known ROI. The method was tested by using 63 MR images of rabbit lumbar disks, which were segmented to detect disk degeneration. An ICC was used to assess the repeatability of this method compared with manual segmentation. The error in the detected area of the rabbit NP by using CS was -3.49% ± 4.4% (mean ± SD) compared with 22.36% ± 5.55% by using manual segmentation. Moreover, the method was capable of detecting disk degeneration in a known rabbit puncture model of disk degeneration. Finally, this method had an ICC of 0.97 and 0.99 in regard to segmenting the area and calculating the MR imaging index of the NP, deeming it highly repeatable. The CS method is a semiautomated computer method able to segment the NP of the rabbit disk and detect disk degeneration. In addition, it could assist in clinical detection, assessment, and monitoring of early degeneration in human disks.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 25%
Student > Master 5 16%
Professor > Associate Professor 4 13%
Student > Ph. D. Student 3 9%
Student > Doctoral Student 2 6%
Other 5 16%
Unknown 5 16%
Readers by discipline Count As %
Medicine and Dentistry 15 47%
Engineering 4 13%
Agricultural and Biological Sciences 3 9%
Veterinary Science and Veterinary Medicine 2 6%
Unknown 8 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 December 2023.
All research outputs
#7,628,840
of 23,248,929 outputs
Outputs from American Journal of Neuroradiology
#2,150
of 4,944 outputs
Outputs of similar age
#34,074
of 95,190 outputs
Outputs of similar age from American Journal of Neuroradiology
#5
of 19 outputs
Altmetric has tracked 23,248,929 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,944 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 49th percentile – i.e., 49% 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 95,190 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.