Overview of the VQA-Med task at ImageCLEF 2020 : visual question answering and generation in the medical domain

Ben Abacha, Asma (National Library of Medicine, USA) ; Datla, Vivek V. (Philips Research Cambridge, USA) ; Hasan, Sadid A. (CVS Health, USA) ; Demner-Fushman, Dina (National Library of Medicine, USA) ; Müller, Henning (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

This paper presents an overview of the Medical Visual Question Answering (VQA-Med) task at ImageCLEF 2020. This third edition of VQA-Med included two tasks: (i) Visual Question Answering (VQA), where participants were tasked with answering abnormality questions from the visual content of radiology images and (ii) Visual Question Generation (VQG), consisting of generating relevant questions about radiology images based on their visual content. In VQA-Med 2020, 11 teams participated in at least one of the two tasks and submitted a total of 62 runs. The best team achieved a BLEU score of 0.542 in the VQA task and 0.348 in the VQG task.


Note: Due to the COVID-19 outbreak, the CLEF 2020 - Conference and Labs of the Evaluation Forum venue in Thessaloniki was cancelled. The proceedings of the online conference are however published according to the original schedule.


Keywords:
Conference Type:
published full paper
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Publisher:
Thessaloniki, Greece, 22-25 September 2020
Date:
2020-09
Thessaloniki, Greece
22-25 September 2020
Pagination:
9 p.
Published in:
Proceedings of the CLEF 2020 - Conference and labs of the evaluation forum
External resources:
Appears in Collection:



 Record created 2020-11-18, last modified 2020-11-20

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