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Validation of Automated White Matter Hyperintensity Segmentation

Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scan...

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Autores principales: Smart, Sean D., Firbank, Michael J., O'Brien, John T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE-Hindawi Access to Research 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3167190/
https://www.ncbi.nlm.nih.gov/pubmed/21904678
http://dx.doi.org/10.4061/2011/391783
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author Smart, Sean D.
Firbank, Michael J.
O'Brien, John T.
author_facet Smart, Sean D.
Firbank, Michael J.
O'Brien, John T.
author_sort Smart, Sean D.
collection PubMed
description Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scans were also segmented in a fully automated fashion by three different programmes. The voxel overlap between manual and automated segmentation was compared. Results. Between observer overlap ratio was 63%. Using our previously described in-house software, we had overlap of 62.2%. We investigated the use of a modified version of SPM segmentation; however, this was not successful, with only 14% overlap. Discussion. Using our previously reported software, we demonstrated good segmentation of WMHs in a fully automated fashion.
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spelling pubmed-31671902011-09-08 Validation of Automated White Matter Hyperintensity Segmentation Smart, Sean D. Firbank, Michael J. O'Brien, John T. J Aging Res Research Article Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scans were also segmented in a fully automated fashion by three different programmes. The voxel overlap between manual and automated segmentation was compared. Results. Between observer overlap ratio was 63%. Using our previously described in-house software, we had overlap of 62.2%. We investigated the use of a modified version of SPM segmentation; however, this was not successful, with only 14% overlap. Discussion. Using our previously reported software, we demonstrated good segmentation of WMHs in a fully automated fashion. SAGE-Hindawi Access to Research 2011 2011-09-06 /pmc/articles/PMC3167190/ /pubmed/21904678 http://dx.doi.org/10.4061/2011/391783 Text en Copyright © 2011 Sean D. Smart et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Smart, Sean D.
Firbank, Michael J.
O'Brien, John T.
Validation of Automated White Matter Hyperintensity Segmentation
title Validation of Automated White Matter Hyperintensity Segmentation
title_full Validation of Automated White Matter Hyperintensity Segmentation
title_fullStr Validation of Automated White Matter Hyperintensity Segmentation
title_full_unstemmed Validation of Automated White Matter Hyperintensity Segmentation
title_short Validation of Automated White Matter Hyperintensity Segmentation
title_sort validation of automated white matter hyperintensity segmentation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3167190/
https://www.ncbi.nlm.nih.gov/pubmed/21904678
http://dx.doi.org/10.4061/2011/391783
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