Evaluating performance of biomedical image retrieval systems--an overview of the medical image retrieval task at ImageCLEF 2004-2013.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Published Date: Mar 27, 2014

Abstract

Medical image retrieval and classification have been extremely active research topics over the past 15 years. Within the ImageCLEF benchmark in medical image retrieval and classification, a standard test bed was created that allows researchers to compare their approaches and ideas on increasingly large and varied data sets including generated ground truth. This article describes the lessons learned in ten evaluation campaigns. A detailed analysis of the data also highlights the value of the resources created.

Authors

  • Jayashree Kalpathy-Cramer
    Department of Radiology, MGH/Harvard Medical School, Charlestown, Massachusetts.
  • Alba García Seco de Herrera
    University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland.
  • Dina Demner-Fushman
    Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD.
  • Sameer Antani
    Computational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
  • Steven Bedrick
    Oregon Health & Science University, Portland, OR, USA.
  • Henning Muller

Keywords

External Resources

Popular Topics
Recent Journals