TY - GEN
T1 - Overview of the ImageCLEFmed 2007 medical retrieval and medical annotation tasks
AU - Müller, Henning
AU - Deselaers, Thomas
AU - Deserno, Thomas M.
AU - Kalpathy-Cramer, Jayashree
AU - Kim, Eugene
AU - Hersh, William
PY - 2008
Y1 - 2008
N2 - This paper describes the medical image retrieval and medical image annotation tasks of ImageCLEF 2007. Separate sections describe each of the two tasks, with the participation and an evaluation of major findings from the results of each given. A total of 13 groups participated in the medical retrieval task and 10 in the medical annotation task. The medical retrieval task added two new data sets for a total of over 66'000 images. Topics were derived from a log file of the Pubmed biomedical literature search system, creating realistic information needs with a clear user model. The medical annotation task was in 2007 organized in a new format as a hierarchical classification had to be performed and classification could be stopped at any hierarchy level. This required algorithms to change significantly and to integrate a confidence level into their decisions to be able to judge where to stop classification to avoid making mistakes in the hierarchy. Scoring took into account errors and unclassified parts.
AB - This paper describes the medical image retrieval and medical image annotation tasks of ImageCLEF 2007. Separate sections describe each of the two tasks, with the participation and an evaluation of major findings from the results of each given. A total of 13 groups participated in the medical retrieval task and 10 in the medical annotation task. The medical retrieval task added two new data sets for a total of over 66'000 images. Topics were derived from a log file of the Pubmed biomedical literature search system, creating realistic information needs with a clear user model. The medical annotation task was in 2007 organized in a new format as a hierarchical classification had to be performed and classification could be stopped at any hierarchy level. This required algorithms to change significantly and to integrate a confidence level into their decisions to be able to judge where to stop classification to avoid making mistakes in the hierarchy. Scoring took into account errors and unclassified parts.
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U2 - 10.1007/978-3-540-85760-0_59
DO - 10.1007/978-3-540-85760-0_59
M3 - Conference contribution
AN - SCOPUS:70349828890
SN - 3540857591
SN - 9783540857594
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 472
EP - 491
BT - Advances in Multilingual and Multimodal Information Retrieval - 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Revised Selected Papers
PB - Springer-Verlag
T2 - 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007
Y2 - 19 September 2007 through 21 September 2007
ER -