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Medical Visual Question Answering: A Survey

2021-11-19 05:55:15
Zhihong Lin, Donghao Zhang, Qingyi Tac, Danli Shi, Gholamreza Haffari, Qi Wu, Mingguang He, Zongyuan Ge
arXiv_AI
           
Abstract

Medical Visual Question Answering (VQA) is a combination of medical artificial intelligence and popular VQA challenges. Given a medical image and a clinically relevant question in natural language, the medical VQA system is expected to predict a plausible and convincing answer. Although the general-domain VQA has been extensively studied, the medical VQA still needs specific investigation and exploration due to its task features. In the first part of this survey, we cover and discuss the publicly available medical VQA datasets up to date about the data source, data quantity, and task feature. In the second part, we review the approaches used in medical VQA tasks. In the last part, we analyze some medical-specific challenges for the field and discuss future research directions.

Abstract (translated)

URL

https://arxiv.org/abs/2111.10056

PDF

https://arxiv.org/pdf/2111.10056.pdf

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