title: Retrieving similar cases from the medical literature - the ImageCLEF experience.
abstract: An increasing number of clinicians, researchers, educators and patients routinely search for relevant medical images using search engines on the internet as well as in image archives and PACS systems. However, image retrieval is far less understood and developed compared to text-based searching. The ImageCLEF medical image retrieval task is an international challenge evaluation that enables researchers to assess and compare techniques for medical image retrieval using test collections. In this paper, we describe the development of the ImageCLEF medical image test collection, consisting of a database of images and their associated annotations, as well as a set of realistic search topics and relevance judgments obtained using a set of experts. 2009 was the sixth year for the ImageCLEF medical retrieval task and had strong participation from research groups across the globe. We will provide results from this year's evaluation and discuss the successes that we have had as well as challenges going forward.
authors.affiliation: Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Sciences University, Portland, OR, USA. kalpathy@ohsu.edu
authors.forename: Jayashree
authors.initials: J
authors.lastname: Kalpathy-Cramer
authors.forename: Steven
authors.initials: S
authors.lastname: Bedrick
authors.forename: Saïd
authors.initials: S
authors.lastname: Radhouani
authors.forename: William
authors.initials: W
authors.lastname: Hersh
authors.forename: Ivan
authors.initials: I
authors.lastname: Eggel
authors.forename: Charles E
authors.initials: CE
authors.lastname: Kahn
authors.forename: Henning
authors.initials: H
authors.lastname: Müller
mesh_terms: D016208:Databases, Factual; D003952:Diagnostic Imaging; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods* / Q000639:trends; D008490:Medical Informatics / Q000379:methods