Automatic knee meniscus tear detection and orientation classification with Mask-RCNN.

Journal: Diagnostic and interventional imaging
Published Date: Mar 23, 2019

Abstract

PURPOSE: This work presents our contribution to a data challenge organized by the French Radiology Society during the Journées Francophones de Radiologie in October 2018. This challenge consisted in classifying MR images of the knee with respect to the presence of tears in the knee menisci, on meniscal tear location, and meniscal tear orientation.

Authors

  • V Couteaux
    Philips Research France, 33, rue de Verdun, 92150 Suresnes, France; LTCI, Télécom ParisTech, Université Paris-Saclay, 75013 Paris, France. Electronic address: vincent.couteaux@telecom-paristech.fr.
  • S Si-Mohamed
    CREATIS, CNRS UMR 5220, Inserm U1206, INSA-Lyon, Claude Bernard Lyon 1 University, 69100 Villeurbanne, France; Department of Radiology, Hospices Civils de Lyon, 69002 Lyon, France.
  • O Nempont
    Philips Research France, 33, rue de Verdun, 92150 Suresnes, France.
  • T Lefevre
    Philips Research France, 33, rue de Verdun, 92150 Suresnes, France.
  • A Popoff
    Philips Research France, 33, rue de Verdun, 92150 Suresnes, France.
  • G Pizaine
    Philips Research France, 33, rue de Verdun, 92150 Suresnes, France.
  • N Villain
    Philips Research France, 33, rue de Verdun, 92150 Suresnes, France.
  • I Bloch
    LTCI, Télécom ParisTech, Université Paris-Saclay, 75013 Paris, France.
  • A Cotten
    Department of Musculoskeletal Radiology, Lille University Hospital, 59037 Lille, France.
  • L Boussel
    Department of radiology, hôpital de la Croix-Rousse, 103, Grande rue de la Croix-Rousse, 69004 Lyon, France; Unité CNRS UMR 5220, CREATIS, Inserm U1206, Insa Lyon, université Lyon 1, université Jean-Monnet Saint-Étienne, 7, avenue Jean-Capelle, 69100 Villeurbanne, France. Electronic address: loic.boussel@chu-lyon.fr.

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