Image retrieval in medicine: The imageCLEF medical image retrieval evaluation

William Hersh, Henning Müller

Research output: Contribution to specialist publicationArticle

2 Scopus citations


The ImageCLEF medical image retrieval challenge evaluation, which has developed test collections for system-oriented evaluation of image retrieval systems and algorithms is discussed. Image retrieval systems take two approaches to indexing and retrieving data that includes indexing and retrieve textual annotations associated with images, and employment of image processing techniques to features in the images. The limitations of purely textual indexing of images for retrieval, such as the inability to capture synonymy, has been described as conceptual relationships or larger themes underlying their content. Health Education Assets Library (HEAL) project focus to standardize the metadata associated with all medical digital objects. The ImageCLEF medical image retrieval tasks have developed a large test collection and attracted research groups who have brought a diverse set of approaches to a common goal of effective image retrieval.

Original languageEnglish (US)
Specialist publicationBulletin of the American Society for Information Science and Technology
StatePublished - Feb 2007

ASJC Scopus subject areas

  • Library and Information Sciences


Dive into the research topics of 'Image retrieval in medicine: The imageCLEF medical image retrieval evaluation'. Together they form a unique fingerprint.

Cite this