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Efficient Web-Based Review for Automatic Segmentation of Volumetric DICOM Images

  • Tobias SteinEmail author
  • Jasmin Metzger
  • Jonas Scherer
  • Fabian Isensee
  • Tobias Norajitra
  • Jens Kleesiek
  • Klaus Maier-Hein
  • Marco Nolden
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

Within a clinical image analysis workflow with large data sets of patient images, the assessment, and review of automatically generated segmentation results by medical experts are time constrained. We present a software system able to inspect such quantitative results in a fast and intuitive way, potentially improving the daily repetitive review work of a research radiologist. Combining established standards with modern technologies creates a flexible environment to efficiently evaluate multiple segmentation algorithm outputs based on different metrics and visualizations and report these analysis results back to a clinical system environment. First experiments show that the time to review automatic segmentation results can be decreased by roughly 50% while the determination of the radiologist is enhanced.

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Copyright information

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

Authors and Affiliations

  • Tobias Stein
    • 1
    Email author
  • Jasmin Metzger
    • 1
  • Jonas Scherer
    • 1
  • Fabian Isensee
    • 1
  • Tobias Norajitra
    • 1
  • Jens Kleesiek
    • 2
  • Klaus Maier-Hein
    • 1
  • Marco Nolden
    • 1
  1. 1.Division of Medical Image ComputingGerman Cancer Research Center (DKFZ)HeidelbergDeutschland
  2. 2.Division of RadiologyGerman Cancer Research Center (DKFZ)HeidelbergDeutschland

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