Detecting Osteophytes in Radiographs of the Knee to Diagnose Osteoarthritis

  • Jessie ThomsonEmail author
  • Terence O’Neill
  • David Felson
  • Tim Cootes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10019)


We present a fully automatic system for identifying osteophytes on knee radiographs, and for estimating the widely used Kellgren-Lawrence (KL) grade for Osteoarthritis (OA). We have compared three advanced modelling and texture techniques. We found that a Random Forest trained using Haar-features achieved good results, but the optimal results are obtained by combining shape modelling and texture features. The system achieves the best reported performance for identifying osteophytes (AUC: 0.85), for measuring KL grades and for classifying OA (AUC: 0.93), with an error rate half that of the previous best method.


Medical image analysis Computer-aided diagnosis 



This report includes independent research funded by the National Institute for Health Research Biomedical Research Unit Funding Scheme. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Jessie Thomson
    • 1
    • 2
    Email author
  • Terence O’Neill
    • 2
    • 3
  • David Felson
    • 2
    • 3
    • 4
  • Tim Cootes
    • 1
  1. 1.Centre for Imaging SciencesUniversity of ManchesterManchesterUK
  2. 2.NIHR Manchester Musculoskeletal BRUCentral Manchester NHS Foundation Trust, MAHSCManchesterUK
  3. 3.Arthritis Research UK Centre for EpidemiologyUniversity of ManchesterManchesterUK
  4. 4.Boston UniversityBostonUSA

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