A Machine-Learning Approach to the Automated Assessment of Joint Synovitis Activity

  • Konrad Wojciechowski
  • Bogdan Smolka
  • Rafal Cupek
  • Adam Ziebinski
  • Karolina Nurzynska
  • Marek Kulbacki
  • Jakub Segen
  • Marcin Fojcik
  • Pawel Mielnik
  • Sebastian Hein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9876)

Abstract

Medical ultrasound imaging is an important tool in diagnosing and monitoring synovitis, which is an inflammation of the synovial membrane that surrounds a joint. Ultrasound images are examined by medical experts to assess the presence and progression of synovitis. Automating image analysis reduces the costs and increases the availability of the ultrasound diagnosis of synovitis and diminishes or eliminates subjective discrepancies. This article describes research that is concerned with the problem of the automatic estimation of the state of the activity of finger joint inflammation using the information that is present in ultrasonography imaging.

Keywords

Arthritis Synovitis 

Notes

Acknowledgement

This research obtained funding from the Norwegian Financial Mechanism 2009–2014 under Project Contract No. Pol-Nor/204256/16/2013. The ultrasound images for the MEDUSA project were created at the Section for Rheumatology; Department for Neurology, Rheumatology and Physical Medicine, 238 Central Hospital, Forde, Norway.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Konrad Wojciechowski
    • 1
  • Bogdan Smolka
    • 2
  • Rafal Cupek
    • 2
  • Adam Ziebinski
    • 2
  • Karolina Nurzynska
    • 2
  • Marek Kulbacki
    • 1
  • Jakub Segen
    • 1
  • Marcin Fojcik
    • 3
  • Pawel Mielnik
    • 4
  • Sebastian Hein
    • 5
  1. 1.Polish-Japanese Institute of Information TechnologyWarsawPoland
  2. 2.Silesian University of TechnologyGliwicePoland
  3. 3.Høgskulen i Sogn og FjordaneSogndalNorway
  4. 4.Helse FørdeFørdeNorway
  5. 5.Medical Technology and Equipment InstituteZabrzePoland

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