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A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain
Diffuse WHO grade II gliomas are diffusively infiltrative brain tumors characterized by an unavoidable anaplastic transformation. Their management is strongly dependent on their location in the brain due to interactions with functional regions and potential differences in molecular biology. In this...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709135/ https://www.ncbi.nlm.nih.gov/pubmed/26751577 http://dx.doi.org/10.1371/journal.pone.0144200 |
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author | Parisot, Sarah Darlix, Amélie Baumann, Cédric Zouaoui, Sonia Yordanova, Yordanka Blonski, Marie Rigau, Valérie Chemouny, Stéphane Taillandier, Luc Bauchet, Luc Duffau, Hugues Paragios, Nikos |
author_facet | Parisot, Sarah Darlix, Amélie Baumann, Cédric Zouaoui, Sonia Yordanova, Yordanka Blonski, Marie Rigau, Valérie Chemouny, Stéphane Taillandier, Luc Bauchet, Luc Duffau, Hugues Paragios, Nikos |
author_sort | Parisot, Sarah |
collection | PubMed |
description | Diffuse WHO grade II gliomas are diffusively infiltrative brain tumors characterized by an unavoidable anaplastic transformation. Their management is strongly dependent on their location in the brain due to interactions with functional regions and potential differences in molecular biology. In this paper, we present the construction of a probabilistic atlas mapping the preferential locations of diffuse WHO grade II gliomas in the brain. This is carried out through a sparse graph whose nodes correspond to clusters of tumors clustered together based on their spatial proximity. The interest of such an atlas is illustrated via two applications. The first one correlates tumor location with the patient’s age via a statistical analysis, highlighting the interest of the atlas for studying the origins and behavior of the tumors. The second exploits the fact that the tumors have preferential locations for automatic segmentation. Through a coupled decomposed Markov Random Field model, the atlas guides the segmentation process, and characterizes which preferential location the tumor belongs to and consequently which behavior it could be associated to. Leave-one-out cross validation experiments on a large database highlight the robustness of the graph, and yield promising segmentation results. |
format | Online Article Text |
id | pubmed-4709135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-47091352016-01-15 A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain Parisot, Sarah Darlix, Amélie Baumann, Cédric Zouaoui, Sonia Yordanova, Yordanka Blonski, Marie Rigau, Valérie Chemouny, Stéphane Taillandier, Luc Bauchet, Luc Duffau, Hugues Paragios, Nikos PLoS One Research Article Diffuse WHO grade II gliomas are diffusively infiltrative brain tumors characterized by an unavoidable anaplastic transformation. Their management is strongly dependent on their location in the brain due to interactions with functional regions and potential differences in molecular biology. In this paper, we present the construction of a probabilistic atlas mapping the preferential locations of diffuse WHO grade II gliomas in the brain. This is carried out through a sparse graph whose nodes correspond to clusters of tumors clustered together based on their spatial proximity. The interest of such an atlas is illustrated via two applications. The first one correlates tumor location with the patient’s age via a statistical analysis, highlighting the interest of the atlas for studying the origins and behavior of the tumors. The second exploits the fact that the tumors have preferential locations for automatic segmentation. Through a coupled decomposed Markov Random Field model, the atlas guides the segmentation process, and characterizes which preferential location the tumor belongs to and consequently which behavior it could be associated to. Leave-one-out cross validation experiments on a large database highlight the robustness of the graph, and yield promising segmentation results. Public Library of Science 2016-01-11 /pmc/articles/PMC4709135/ /pubmed/26751577 http://dx.doi.org/10.1371/journal.pone.0144200 Text en © 2016 Parisot et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Parisot, Sarah Darlix, Amélie Baumann, Cédric Zouaoui, Sonia Yordanova, Yordanka Blonski, Marie Rigau, Valérie Chemouny, Stéphane Taillandier, Luc Bauchet, Luc Duffau, Hugues Paragios, Nikos A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain |
title | A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain |
title_full | A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain |
title_fullStr | A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain |
title_full_unstemmed | A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain |
title_short | A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain |
title_sort | probabilistic atlas of diffuse who grade ii glioma locations in the brain |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709135/ https://www.ncbi.nlm.nih.gov/pubmed/26751577 http://dx.doi.org/10.1371/journal.pone.0144200 |
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