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Reducing acquisition time for MRI-based forensic age estimation

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 i...

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Autores principales: Neumayer, Bernhard, Schloegl, Matthias, Payer, Christian, Widek, Thomas, Tschauner, Sebastian, Ehammer, Thomas, Stollberger, Rudolf, Urschler, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794919/
https://www.ncbi.nlm.nih.gov/pubmed/29391552
http://dx.doi.org/10.1038/s41598-018-20475-1
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author Neumayer, Bernhard
Schloegl, Matthias
Payer, Christian
Widek, Thomas
Tschauner, Sebastian
Ehammer, Thomas
Stollberger, Rudolf
Urschler, Martin
author_facet Neumayer, Bernhard
Schloegl, Matthias
Payer, Christian
Widek, Thomas
Tschauner, Sebastian
Ehammer, Thomas
Stollberger, Rudolf
Urschler, Martin
author_sort Neumayer, Bernhard
collection PubMed
description 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.
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spelling pubmed-57949192018-02-12 Reducing acquisition time for MRI-based forensic age estimation Neumayer, Bernhard Schloegl, Matthias Payer, Christian Widek, Thomas Tschauner, Sebastian Ehammer, Thomas Stollberger, Rudolf Urschler, Martin Sci Rep Article 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. Nature Publishing Group UK 2018-02-01 /pmc/articles/PMC5794919/ /pubmed/29391552 http://dx.doi.org/10.1038/s41598-018-20475-1 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Neumayer, Bernhard
Schloegl, Matthias
Payer, Christian
Widek, Thomas
Tschauner, Sebastian
Ehammer, Thomas
Stollberger, Rudolf
Urschler, Martin
Reducing acquisition time for MRI-based forensic age estimation
title Reducing acquisition time for MRI-based forensic age estimation
title_full Reducing acquisition time for MRI-based forensic age estimation
title_fullStr Reducing acquisition time for MRI-based forensic age estimation
title_full_unstemmed Reducing acquisition time for MRI-based forensic age estimation
title_short Reducing acquisition time for MRI-based forensic age estimation
title_sort reducing acquisition time for mri-based forensic age estimation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794919/
https://www.ncbi.nlm.nih.gov/pubmed/29391552
http://dx.doi.org/10.1038/s41598-018-20475-1
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