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The Digital Brain Tumour Atlas, an open histopathology resource
Currently, approximately 150 different brain tumour types are defined by the WHO. Recent endeavours to exploit machine learning and deep learning methods for supporting more precise diagnostics based on the histological tumour appearance have been hampered by the relative paucity of accessible digit...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847577/ https://www.ncbi.nlm.nih.gov/pubmed/35169150 http://dx.doi.org/10.1038/s41597-022-01157-0 |
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author | Roetzer-Pejrimovsky, Thomas Moser, Anna-Christina Atli, Baran Vogel, Clemens Christian Mercea, Petra A. Prihoda, Romana Gelpi, Ellen Haberler, Christine Höftberger, Romana Hainfellner, Johannes A. Baumann, Bernhard Langs, Georg Woehrer, Adelheid |
author_facet | Roetzer-Pejrimovsky, Thomas Moser, Anna-Christina Atli, Baran Vogel, Clemens Christian Mercea, Petra A. Prihoda, Romana Gelpi, Ellen Haberler, Christine Höftberger, Romana Hainfellner, Johannes A. Baumann, Bernhard Langs, Georg Woehrer, Adelheid |
author_sort | Roetzer-Pejrimovsky, Thomas |
collection | PubMed |
description | Currently, approximately 150 different brain tumour types are defined by the WHO. Recent endeavours to exploit machine learning and deep learning methods for supporting more precise diagnostics based on the histological tumour appearance have been hampered by the relative paucity of accessible digital histopathological datasets. While freely available datasets are relatively common in many medical specialties such as radiology and genomic medicine, there is still an unmet need regarding histopathological data. Thus, we digitized a significant portion of a large dedicated brain tumour bank based at the Division of Neuropathology and Neurochemistry of the Medical University of Vienna, covering brain tumour cases from 1995–2019. A total of 3,115 slides of 126 brain tumour types (including 47 control tissue slides) have been scanned. Additionally, complementary clinical annotations have been collected for each case. In the present manuscript, we thoroughly discuss this unique dataset and make it publicly available for potential use cases in machine learning and digital image analysis, teaching and as a reference for external validation. |
format | Online Article Text |
id | pubmed-8847577 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88475772022-03-04 The Digital Brain Tumour Atlas, an open histopathology resource Roetzer-Pejrimovsky, Thomas Moser, Anna-Christina Atli, Baran Vogel, Clemens Christian Mercea, Petra A. Prihoda, Romana Gelpi, Ellen Haberler, Christine Höftberger, Romana Hainfellner, Johannes A. Baumann, Bernhard Langs, Georg Woehrer, Adelheid Sci Data Data Descriptor Currently, approximately 150 different brain tumour types are defined by the WHO. Recent endeavours to exploit machine learning and deep learning methods for supporting more precise diagnostics based on the histological tumour appearance have been hampered by the relative paucity of accessible digital histopathological datasets. While freely available datasets are relatively common in many medical specialties such as radiology and genomic medicine, there is still an unmet need regarding histopathological data. Thus, we digitized a significant portion of a large dedicated brain tumour bank based at the Division of Neuropathology and Neurochemistry of the Medical University of Vienna, covering brain tumour cases from 1995–2019. A total of 3,115 slides of 126 brain tumour types (including 47 control tissue slides) have been scanned. Additionally, complementary clinical annotations have been collected for each case. In the present manuscript, we thoroughly discuss this unique dataset and make it publicly available for potential use cases in machine learning and digital image analysis, teaching and as a reference for external validation. Nature Publishing Group UK 2022-02-15 /pmc/articles/PMC8847577/ /pubmed/35169150 http://dx.doi.org/10.1038/s41597-022-01157-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Roetzer-Pejrimovsky, Thomas Moser, Anna-Christina Atli, Baran Vogel, Clemens Christian Mercea, Petra A. Prihoda, Romana Gelpi, Ellen Haberler, Christine Höftberger, Romana Hainfellner, Johannes A. Baumann, Bernhard Langs, Georg Woehrer, Adelheid The Digital Brain Tumour Atlas, an open histopathology resource |
title | The Digital Brain Tumour Atlas, an open histopathology resource |
title_full | The Digital Brain Tumour Atlas, an open histopathology resource |
title_fullStr | The Digital Brain Tumour Atlas, an open histopathology resource |
title_full_unstemmed | The Digital Brain Tumour Atlas, an open histopathology resource |
title_short | The Digital Brain Tumour Atlas, an open histopathology resource |
title_sort | digital brain tumour atlas, an open histopathology resource |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847577/ https://www.ncbi.nlm.nih.gov/pubmed/35169150 http://dx.doi.org/10.1038/s41597-022-01157-0 |
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