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

Jayashree Kalpathy-Cramer, Alba García Seco de Herrera, Dina Demner-Fushman, Sameer Antani, Steven Bedrick, Henning Müller

Research output: Contribution to journalArticle

78 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)55-61
Number of pages7
JournalComputerized Medical Imaging and Graphics
Volume39
DOIs
StatePublished - Jan 1 2015

Keywords

  • Biomedical literature
  • Content-based retrieval
  • Image retrieval
  • Multimodal medical retrieval
  • Text-based image retrieval

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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