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

doi:10.1016/j.compmedimag.2014.03.004

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

Institute on Development and Disability

Research output: Contribution to journal › Article › peer-review

119 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 language	English (US)
Pages (from-to)	55-61
Number of pages	7
Journal	Computerized Medical Imaging and Graphics
Volume	39
DOIs	https://doi.org/10.1016/j.compmedimag.2014.03.004
State	Published - 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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10.1016/j.compmedimag.2014.03.004

Cite this

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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.",

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AU - Demner-Fushman, Dina

AU - Antani, Sameer

AU - Bedrick, Steven

AU - Müller, Henning

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KW - Biomedical literature

KW - Content-based retrieval

KW - Image retrieval

KW - Multimodal medical retrieval

KW - Text-based image retrieval

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

Abstract

Keywords

ASJC Scopus subject areas

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