Applying cascaded convolutional neural network design further enhances automatic scoring of arthritis disease activity on ultrasound images from rheumatoid arthritis patients.

Journal: Annals of the rheumatic diseases
Published Date:

Abstract

OBJECTIVES: We have previously shown that neural network technology can be used for scoring arthritis disease activity in ultrasound images from rheumatoid arthritis (RA) patients, giving scores according to the EULAR-OMERACT grading system. We have now further developed the architecture of this neural network and can here present a new idea applying cascaded convolutional neural network (CNN) design with even better results. We evaluate the generalisability of this method on unseen data, comparing the CNN with an expert rheumatologist.

Authors

  • Anders Bossel Holst Christensen
    Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark abc@mmmi.sdu.dk.
  • Søren Andreas Just
    Department of Rheumatology, Odense Universitetshospital, Odense, Denmark.
  • Jakob Kristian Holm Andersen
    The Maersk Mc-Kinney Moller Institute, Syddansk Universitet, Odense, Denmark.
  • Thiusius Rajeeth Savarimuthu
    The Maersk Mc-Kinney Moller Institute, Syddansk Universitet, Odense, Denmark.