articleJul 1, 2017GREEN OA

ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

XWXiaosong WangYPYifan PengLLLe LuZLZhiyong LuMBMohammadhadi Bagheri

National Center for Biotechnology Information · National Institutes of Health

Indexed inarxivcrossref

Abstract

The chest X-ray is one of the most commonly accessible radiological examinations for screening and diagnosis of many lung diseases. A tremendous number of X-ray imaging studies accompanied by radiological reports are accumulated and stored in many modern hospitals Picture Archiving and Communication Systems (PACS). On the other side, it is still an open question how this type of hospital-size knowledge database containing invaluable imaging informatics (i.e., loosely labeled) can be used to facilitate the data-hungry deep learning paradigms in building truly large-scale high precision computer-aided diagnosis (CAD) systems. In this paper, we present a new chest X-ray database, namely ChestX-ray8, which…

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3,289
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Authors

6
  • XW
    Xiaosong WangCorresponding
  • YP
    Yifan Peng

    National Center for Biotechnology Information, National Institutes of Health

  • LL
    Le Lu
  • ZL
    Zhiyong Lu

    National Center for Biotechnology Information, National Institutes of Health

  • MB
    Mohammadhadi Bagheri

Topics & keywords

Keywords
  • Convolutional neural network
  • Radiological weapon
  • Thorax (insect anatomy)
  • Thoracic diseases
  • Medical imaging
  • Contextual image classification
  • Deep learning
  • DICOM
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