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Overview of the ImageCLEF 2016 Medical Task

Garcia Seco De Herrera, Alba and Schaer, Roger and Bromuri, Stefano and Müller, Henning (2016) Overview of the ImageCLEF 2016 Medical Task. In: CLEF 2016 - Conference and Labs of the Evaluation forum, 2016-09-05 - 2016-09-08, Évora, Portugal.

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Abstract

ImageCLEF is the image retrieval task of the Conference and Labs of the Evaluation Forum (CLEF). ImageCLEF has historically focused on the multimodal and language–independent retrieval of images. Many tasks are related to image classification and the annotation of image data as well. The medical task has focused more on image retrieval in the beginning and then retrieval and classification tasks in subsequent years. In 2016 a main focus was the creation of meta data for a collection of medical images taken from articles of the the biomedical scientific literature. In total 8 teams participated in the four tasks and 69 runs were submitted. No team participated in the caption prediction task, a totally new task. Deep learning has now been used for several of the ImageCLEF tasks and by many of the participants obtaining very good results. A majority of runs was submitting using deep learning and this follows general trends in machine learning. In several of the tasks multimodal approaches clearly led to best results.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Working Notes of CLEF 2016 - Conference and Labs of the Evaluation forum
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 22 Jan 2020 13:55
Last Modified: 22 Jan 2020 14:15
URI: http://repository.essex.ac.uk/id/eprint/22221

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