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Abstract: Does Bone Suppression and Lung Detection Improve Chest Disease Classification?

  • Ivo M. BaltruschatEmail author
  • Leonhard A. Steinmeister
  • Harald Ittrich
  • Gerhard Adam
  • Hannes Nickisch
  • Axel Saalbach
  • Jens von Berg
  • Michael Grass
  • Tobias Knopp
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

Chest radiography is the most common clinical examination type. To improve the quality of patient care and to reduce workload, researchers started developing methods for automatic pathology classification. In our paper [1], we investigate the effect of advanced image processing techniques – initially developed to support radiologists – on the performance of deep learning techniques.

Literatur

  1. 1.
    Baltruschat IM, Steinmeister LA, Ittrich H, et al. When does bone suppression and lung field segmentation improve chest X-ray disease classification? Proc ISBI. 2019;.Google Scholar
  2. 2.
    Demner-Fushman D, Kohli MD, et al. Preparing a collection of radiology examinations for distribution and retrieval. J Am Med Inform Assoc. 2015; p. 304–310.CrossRefGoogle Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Ivo M. Baltruschat
    • 1
    • 2
    • 3
    • 4
    Email author
  • Leonhard A. Steinmeister
    • 1
    • 3
  • Harald Ittrich
    • 1
  • Gerhard Adam
    • 1
  • Hannes Nickisch
    • 4
  • Axel Saalbach
    • 4
  • Jens von Berg
    • 4
  • Michael Grass
    • 4
  • Tobias Knopp
    • 1
    • 2
  1. 1.Department for Diagnostic and Interventional Radiology and Nuclear MedicineUniversity Medical Center Hamburg-EppendorfHamburgDeutschland
  2. 2.Institute for Biomedical ImagingHamburg University of TechnologyHamburgDeutschland
  3. 3.DAISYLabsForschungszentrum Medizintechnik HamburgHamburgDeutschland
  4. 4.Philips ResearchHamburgDeutschland

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