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Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR
White matter hyperintensities (WMH) seen on T2WI are a hallmark of multiple sclerosis (MS) as it indicates inflammation associated with the disease. Automatic detection of the WMH can be valuable in diagnosing and monitoring of treatment effectiveness. T2 fluid attenuated inversion recovery (FLAIR)...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4130152/ https://www.ncbi.nlm.nih.gov/pubmed/25136355 http://dx.doi.org/10.1155/2014/239123 |
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author | Zhong, Yi Utriainen, David Wang, Ying Kang, Yan Haacke, E. Mark |
author_facet | Zhong, Yi Utriainen, David Wang, Ying Kang, Yan Haacke, E. Mark |
author_sort | Zhong, Yi |
collection | PubMed |
description | White matter hyperintensities (WMH) seen on T2WI are a hallmark of multiple sclerosis (MS) as it indicates inflammation associated with the disease. Automatic detection of the WMH can be valuable in diagnosing and monitoring of treatment effectiveness. T2 fluid attenuated inversion recovery (FLAIR) MR images provided good contrast between the lesions and other tissue; however the signal intensity of gray matter tissue was close to the lesions in FLAIR images that may cause more false positives in the segment result. We developed and evaluated a tool for automated WMH detection only using high resolution 3D T2 fluid attenuated inversion recovery (FLAIR) MR images. We use a high spatial frequency suppression method to reduce the gray matter area signal intensity. We evaluate our method in 26 MS patients and 26 age matched health controls. The data from the automated algorithm showed good agreement with that from the manual segmentation. The linear correlation between these two approaches in comparing WMH volumes was found to be Y = 1.04X + 1.74 (R (2) = 0.96). The automated algorithm estimates the number, volume, and category of WMH. |
format | Online Article Text |
id | pubmed-4130152 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41301522014-08-18 Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR Zhong, Yi Utriainen, David Wang, Ying Kang, Yan Haacke, E. Mark Int J Biomed Imaging Research Article White matter hyperintensities (WMH) seen on T2WI are a hallmark of multiple sclerosis (MS) as it indicates inflammation associated with the disease. Automatic detection of the WMH can be valuable in diagnosing and monitoring of treatment effectiveness. T2 fluid attenuated inversion recovery (FLAIR) MR images provided good contrast between the lesions and other tissue; however the signal intensity of gray matter tissue was close to the lesions in FLAIR images that may cause more false positives in the segment result. We developed and evaluated a tool for automated WMH detection only using high resolution 3D T2 fluid attenuated inversion recovery (FLAIR) MR images. We use a high spatial frequency suppression method to reduce the gray matter area signal intensity. We evaluate our method in 26 MS patients and 26 age matched health controls. The data from the automated algorithm showed good agreement with that from the manual segmentation. The linear correlation between these two approaches in comparing WMH volumes was found to be Y = 1.04X + 1.74 (R (2) = 0.96). The automated algorithm estimates the number, volume, and category of WMH. Hindawi Publishing Corporation 2014 2014-07-22 /pmc/articles/PMC4130152/ /pubmed/25136355 http://dx.doi.org/10.1155/2014/239123 Text en Copyright © 2014 Yi Zhong 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 Zhong, Yi Utriainen, David Wang, Ying Kang, Yan Haacke, E. Mark Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR |
title | Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR |
title_full | Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR |
title_fullStr | Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR |
title_full_unstemmed | Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR |
title_short | Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR |
title_sort | automated white matter hyperintensity detection in multiple sclerosis using 3d t2 flair |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4130152/ https://www.ncbi.nlm.nih.gov/pubmed/25136355 http://dx.doi.org/10.1155/2014/239123 |
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