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

Kalpathy-Cramer, Jayashree ( University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; García Seco de Herrera, Alba ( University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Demner-Fushman, Dina ( University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Antani, Sameer (Antani, Sameer) ; Bedrick, Steven ( University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Müller, Henning ( University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

Medical image retrieval and classification have been extremely active research topics over the past 15 years. With 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 evaluations campaigns. A detailed analysis of the data also highlights the value of the resources created.


Article Type:
scientifique
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Date:
2015
Published in
Computerized medical imaging and graphics
Numeration (vol. no.):
January 2015, vol. 39. no. 55-61, 15 p.
DOI:
ISSN:
0895-6111
Appears in Collection:



 Record created 2015-11-19, last modified 2018-12-20

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