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Reducing acquisition time for MRI-based forensic age estimation

Overview of attention for article published in Scientific Reports, February 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
3 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
19 Mendeley
Title
Reducing acquisition time for MRI-based forensic age estimation
Published in
Scientific Reports, February 2018
DOI 10.1038/s41598-018-20475-1
Pubmed ID
Authors

Bernhard Neumayer, Matthias Schloegl, Christian Payer, Thomas Widek, Sebastian Tschauner, Thomas Ehammer, Rudolf Stollberger, Martin Urschler

Abstract

Radiology-based estimation of a living person's unknown age has recently attracted increasing attention due to large numbers of undocumented immigrants entering Europe. To avoid the application of X-ray-based imaging techniques, magnetic resonance imaging (MRI) has been suggested as an alternative imaging modality. Unfortunately, MRI requires prolonged acquisition times, which potentially represents an additional stressor for young refugees. To eliminate this shortcoming, we investigated the degree of reduction in acquisition time that still led to reliable age estimates. Two radiologists randomly assessed original images and two sets of retrospectively undersampled data of 15 volunteers (N = 45 data sets) applying an established radiological age estimation method to images of the hand and wrist. Additionally, a neural network-based age estimation method analyzed four sets of further undersampled images from the 15 volunteers (N = 105 data sets). Furthermore, we compared retrospectively undersampled and acquired undersampled data for three volunteers. To assess reliability with increasing degree of undersampling, intra-rater and inter-rater agreement were analyzed computing signed differences and intra-class correlation. While our findings have to be confirmed by a larger prospective study, the results from both radiological and automatic age estimation showed that reliable age estimation was still possible for acquisition times of 15 seconds.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 21%
Researcher 4 21%
Student > Bachelor 3 16%
Student > Ph. D. Student 2 11%
Lecturer > Senior Lecturer 1 5%
Other 2 11%
Unknown 3 16%
Readers by discipline Count As %
Medicine and Dentistry 6 32%
Engineering 4 21%
Computer Science 3 16%
Agricultural and Biological Sciences 1 5%
Nursing and Health Professions 1 5%
Other 0 0%
Unknown 4 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 05 March 2018.
All research outputs
#1,933,984
of 13,789,144 outputs
Outputs from Scientific Reports
#15,091
of 68,967 outputs
Outputs of similar age
#66,999
of 356,494 outputs
Outputs of similar age from Scientific Reports
#1
of 14 outputs
Altmetric has tracked 13,789,144 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 68,967 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has done well, scoring higher than 78% 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 356,494 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 81% of its contemporaries.
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 has done particularly well, scoring higher than 92% of its contemporaries.