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.
|Title of host publication||2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021|
|Publisher||IEEE Computer Society|
|Number of pages||5|
|Publication status||Published - 13 Apr 2021|
|Event||18th IEEE International Symposium on Biomedical Imaging, ISBI 2021 - Nice, France|
Duration: 13 Apr 2021 → 16 Apr 2021
|Name||Proceedings - International Symposium on Biomedical Imaging|
|Conference||18th IEEE International Symposium on Biomedical Imaging, ISBI 2021|
|Period||13/04/21 → 16/04/21|
- Medical visual question answering
- Multi-modality fusion.
ASJC Scopus subject areas
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging