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Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme
Glioblastoma multiforme (GBM) is characterized by high infiltration. The interpretation of MRSI data, especially for GBMs, is still challenging. Unsupervised methods based on NMF by Li et al. (2013, NMR in Biomedicine) and Li et al. (2013, IEEE Transactions on Biomedical Engineering) have been propo...
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/PMC3958772/ https://www.ncbi.nlm.nih.gov/pubmed/24724098 http://dx.doi.org/10.1155/2014/762126 |
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author | Li, Yuqian Pi, Yiming Liu, Xin Liu, Yuhan Van Cauter, Sofie |
author_facet | Li, Yuqian Pi, Yiming Liu, Xin Liu, Yuhan Van Cauter, Sofie |
author_sort | Li, Yuqian |
collection | PubMed |
description | Glioblastoma multiforme (GBM) is characterized by high infiltration. The interpretation of MRSI data, especially for GBMs, is still challenging. Unsupervised methods based on NMF by Li et al. (2013, NMR in Biomedicine) and Li et al. (2013, IEEE Transactions on Biomedical Engineering) have been proposed for glioma recognition, but the tissue types is still not well interpreted. As an extension of the previous work, a tissue type assignment method is proposed for GBMs based on the analysis of MRSI data and tissue distribution information. The tissue type assignment method uses the values from the distribution maps of all three tissue types to interpret all the information in one new map and color encodes each voxel to indicate the tissue type. Experiments carried out on in vivo MRSI data show the feasibility of the proposed method. This method provides an efficient way for GBM tissue type assignment and helps to display information of MRSI data in a way that is easy to interpret. |
format | Online Article Text |
id | pubmed-3958772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-39587722014-04-10 Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme Li, Yuqian Pi, Yiming Liu, Xin Liu, Yuhan Van Cauter, Sofie Biomed Res Int Research Article Glioblastoma multiforme (GBM) is characterized by high infiltration. The interpretation of MRSI data, especially for GBMs, is still challenging. Unsupervised methods based on NMF by Li et al. (2013, NMR in Biomedicine) and Li et al. (2013, IEEE Transactions on Biomedical Engineering) have been proposed for glioma recognition, but the tissue types is still not well interpreted. As an extension of the previous work, a tissue type assignment method is proposed for GBMs based on the analysis of MRSI data and tissue distribution information. The tissue type assignment method uses the values from the distribution maps of all three tissue types to interpret all the information in one new map and color encodes each voxel to indicate the tissue type. Experiments carried out on in vivo MRSI data show the feasibility of the proposed method. This method provides an efficient way for GBM tissue type assignment and helps to display information of MRSI data in a way that is easy to interpret. Hindawi Publishing Corporation 2014 2014-03-03 /pmc/articles/PMC3958772/ /pubmed/24724098 http://dx.doi.org/10.1155/2014/762126 Text en Copyright © 2014 Yuqian Li 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 Li, Yuqian Pi, Yiming Liu, Xin Liu, Yuhan Van Cauter, Sofie Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme |
title | Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme |
title_full | Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme |
title_fullStr | Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme |
title_full_unstemmed | Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme |
title_short | Data Analysis and Tissue Type Assignment for Glioblastoma Multiforme |
title_sort | data analysis and tissue type assignment for glioblastoma multiforme |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3958772/ https://www.ncbi.nlm.nih.gov/pubmed/24724098 http://dx.doi.org/10.1155/2014/762126 |
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