A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy
Dataset on Hugging Face
Original Image Download (Simula Datasets)
🚧 Work in Progress
This repository is under active development. The dataset generation code, augmentation scripts, and evaluation tools will be released soon.
If you urgently need access or have questions, please contact:
📧 sushant@simula.no
Kvasir-VQA-x1 is a multimodal dataset aimed at advancing medical visual question answering (MedVQA) in GI endoscopy. We build on the original Kvasir-VQA by adding 159,549 new QA pairs with richer reasoning and complexity stratification.
This repo provides:
- Augmentation scripts
- Dataset generation code
- JSON validators
- Sample training/evaluation workflows
- Metric visualizations (e.g., radar plots)
Each sample includes:
| Field | Description |
|---|---|
img_id |
Image reference from Kvasir-VQA |
complexity |
Reasoning complexity (1–3) |
question |
Natural language QA |
answer |
Human-validated clinical answer |
original |
Source atomic QA pairs |
question_class |
Clinical categories (e.g., polyp type) |
See full dataset: Hugging Face page
- Standard: QA on original images
- Transformed: QA on visually perturbed images (augmented via scripts here)
You can download the original images directly from the official Simula site:
➡️ https://datasets.simula.no/kvasir-vqa/
This dataset is released under CC BY-NC 4.0.
Please cite the associated dataset paper if you use Kvasir-VQA-x1 in your work (coming soon).