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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.
Afiliação
  • Roetzer-Pejrimovsky T; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria. thomas.roetzer-pejrimovsky@meduniwien.ac.at.
  • Moser AC; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Atli B; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Vogel CC; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Mercea PA; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Prihoda R; Department of Neurosurgery, Medical University of Vienna, Vienna, Austria.
  • Gelpi E; Department of Neurosurgery, Medical University of Vienna, Vienna, Austria.
  • Haberler C; Department of Neurosurgery, University Hospital St. Poelten, St. Poelten, Austria.
  • Höftberger R; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Hainfellner JA; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Baumann B; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Langs G; Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Woehrer A; Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
Sci Data ; 9(1): 55, 2022 02 15.
Article em En | MEDLINE | ID: mdl-35169150
ABSTRACT
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas Limite: Humans Idioma: En Revista: Sci Data Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Áustria

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas Limite: Humans Idioma: En Revista: Sci Data Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Áustria
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