Datasets › DME VQA dataset

DME VQA dataset (Diabetic Macular Edema VQA dataset)

Introduced by Sergio Tascon-Morales et al. in Consistency-preserving Visual Question Answering in Medical Imaging27 Jun 2022 archive 2025-07-28

Medical VQA dataset built from the IDRiD and eOphta datasets. The dataset contains both healthy and unhealthy fundus images. For each image, a set of pre-defined questions is generated, including questions about regions (e.g. are there hard exudates in this region?), for which an associated mask denotes the location of the region.

The motivation for this dataset include the lack of public medical VQA datasets with related questions. In our dataset, questions are related because there is a high-level question about the DME grade of the image, and associated low-level questions that can lead to the answer of the high-level question. This allows to study the consistency of a VQA model i.e. how often the model produces contradictory answers to questions about a given image. Questions about regions are also a novel feature of this dataset.

The dataset can be used for general VQA purposes, and also for the more specific purpose of consistency improvement.

Number of images : Train: 433 Val: 112 Test: 134

Number of QA pairs: Train: 9779 Val: 2380 Test: 1311

To download the dataset, click here.

For more information, check our paper.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC BY

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • DME VQA dataset

1 variant name, as the archive lists them.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections