Overview of the ImageCLEF 2015 medical classification task

Müller, Henning (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)) ; Bromuri, Stefano (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

This articles describes the ImageCLEF 2015 Medical Classification task. The task contains several subtasks that all use a data set of figures from the biomedical open access literature (PubMed Central). Particularly compound figures are targeted that are frequent in the literature. For more detailed information analysis and retrieval it is important to extract targeted information from the compound figures. The proposed tasks include compound figure detection (separating compound from other figures), multi-label classification (define all sub types present), figure separation (find boundaries of the subfigures) and modality classification (detecting the figure type of each subfigure). The tasks are described with the participation of international research groups in the tasks. The results of the participants are then described and analysed to identify promising techniques.


Keywords:
Conference Type:
full paper
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Publisher:
Toulouse, France, 8–11 September 2015
Date:
Toulouse, France
8–11 September 2015
2015
Pagination:
13 p.
Published in:
Workshop proceedings of the 6th International Conference and Labs of the Evaluation Forum Association 2015 : Experimental IR Meets Multilinguality, Multimodality, and Interaction
Numeration (vol. no.):
1391
ISSN:
1613-0073
Appears in Collection:



 Record created 2015-11-15, last modified 2019-06-11

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