Medical visual question answering (Med-VQA) has tremendous potential in healthcare. However, the development of this technology is hindered by the lacking of publicly-available and high-quality labeled datasets for training and evaluation. In this paper, we present a large bilingual dataset, SLAKE, with comprehensive semantic labels annotated by experienced physicians and a new structural medical knowledge base for Med-VQA. Besides, SLAKE includes richer modalities and covers more human body parts than the currently available dataset. We show that SLAKE can be used to facilitate the development and evaluation of Med-VQA systems. The dataset can be downloaded from http://www.med-vqa.com/slake.
翻译：医学直观回答(Med-VQA)在医疗保健方面具有巨大的潜力,然而,由于缺乏可供公众获取的高质量有标签的培训和评估数据集,这一技术的开发受到阻碍,我们在本文件中提供了一套大型双语数据集,SLAKE, 配有由有经验的医生加注的综合语义标签,以及Med-VQA的一个新的结构医学知识库。此外,SLAKE还包含比现有数据集更丰富的方式和涵盖更多的人体器官部分。我们表明,SLAKE可用于促进Med-VQA系统的开发和评估。该数据集可从http://www.med-Vqa.com/slake下载。
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