Overview of the VQA-Med Task at ImageCLEF 2020: Visual Question Answering and Generation in the Medical Domain

Asma Ben Abacha Vivek V. Datla2 Sadid A. Hasan3 Dina Demner-Fushman1
and Henning M¨uller4


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.

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