The ImageCLEFmed Medical Image Retrieval Task Test Collection

A growing number of clinicians, educators, researchers, and others use digital images in their work and search for them via image retrieval systems. Yet, this area of information retrieval is much less understood and developed than searching for text-based content, such as biomedical literature and its derivations. The goal of the ImageCLEF medical image retrieval task (ImageCLEFmed) is to improve understanding and system capability in search for medical images. In this paper, we describe the development and use of a medical image test collection designed to facilitate research with image retrieval systems and their users. We also provide baseline results with the new collection and describe them in the context of past research with portions of the collection.

[1]  William R Hersh,et al.  Enhancing access to the Bibliome: the TREC 2004 Genomics Track , 2006, Journal of biomedical discovery and collaboration.

[2]  William R. Hersh,et al.  Medical Image Retrieval and Automatic Annotation: OHSU at ImageCLEF 2007 , 2007, CLEF.

[3]  Hermann Ney,et al.  FIRE in ImageCLEF 2007 , 2007, CLEF.

[4]  Otis Gospodnetic,et al.  Lucene in Action , 2004 .

[5]  Joo-Hwee Lim,et al.  A Structured Visual Learning Approach Mixed with Ontology Dimensions for Medical Queries , 2005, CLEF.

[6]  Fredric C. Gey,et al.  Accessing Multilingual Information Repositories (6th Workshop of the Cross-Language Evaluation Forum, CLEF 2005) , 2006 .

[7]  Patrick Ruch,et al.  Model Formulation: Advancing Biomedical Image Retrieval: Development and Analysis of a Test Collection , 2006, J. Am. Medical Informatics Assoc..

[8]  Carol Peters,et al.  Cross-Language Evaluation Forum: Objectives, Results, Achievements , 2004, Information Retrieval.

[9]  Joo-Hwee Lim,et al.  Medical-Image Retrieval Based on Knowledge-Assisted Text and Image Indexing , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  Paul Over,et al.  Interactivity at the Text Retrieval Conference (TREC) , 2001, Inf. Process. Manag..

[11]  Karen Spärck Jones Reflections on TREC , 1995, Inf. Process. Manag..

[12]  Patrick Ruch,et al.  A Qualitative Task Analysis of Biomedical Image Use and Retrieval , 2005 .

[13]  William R. Hersh,et al.  Automatic Image Modality Based Classification and Annotation to Improve Medical Image Retrieval , 2007, MedInfo.

[14]  Cheng Thao,et al.  GoldMiner: a radiology image search engine. , 2007, AJR. American journal of roentgenology.

[15]  William R. Hersh,et al.  Manual Query Modification and Data Fusion for Medical Image Retrieval , 2005, CLEF.

[16]  Chris Buckley,et al.  OHSUMED: an interactive retrieval evaluation and new large test collection for research , 1994, SIGIR '94.

[17]  Ellen M. Voorhees,et al.  Retrieval System Evaluation , 2005 .

[18]  Henning Müllera,et al.  Health care professionals ’ image use and search behaviour , 2006 .

[19]  Fredric C. Gey,et al.  ENSM-SE at CLEF 2006 : Fuzzy Proximity Method with an Adhoc Influence Function in Evaluation of Multilingual and Multi-modal Information Retrieval 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain , 2007 .

[20]  José Luis Vicedo González,et al.  TREC: Experiment and evaluation in information retrieval , 2007, J. Assoc. Inf. Sci. Technol..

[21]  William R. Hersh,et al.  Medical Image Retrieval and Automated Annotation: OHSU at ImageCLEF 2006 , 2006, CLEF.

[22]  Thomas Deselaers,et al.  Overview of the ImageCLEF 2006 Photographic Retrieval and Object Annotation Tasks , 2006, CLEF.

[23]  Christian Lovis,et al.  The Use of MedGIFT and EasyIR for ImageCLEF 2005 , 2005, CLEF.

[24]  Joo-Hwee Lim,et al.  IPAL Knowledge-based Medical Image Retrieval in ImageCLEFmed 2006 , 2006, CLEF.