README.md

---
license: cc-by-nc-4.0
task_categories:
- image-classification
language:
- en
tags:
- medical
size_categories:
- 10K<n<100K
---
# FLARE25 Medical Multimodal Dataset

This repository contains a multimodal medical imaging dataset for FLARE 2025 with question-answer pairs across various medical imaging modalities.

<div style="text-align: center;">
  <img src="https://iili.io/FYrlgdG.md.png" style="max-width: 90%; height: auto;" alt="Description">
</div>

## Dataset Structure

The dataset is organized into the following main directories:

- `training/`: Training data
- `validation-public/`: Public validation data
- `validation-hidden/`: Hidden validation data (answer not released)
- `testing/`: Hidden testing data (not released)

## Dataset Statistics

- **Total datasets:** 19
- **Medical imaging modalities:** 8
- **Task types:** 10
- **Total images:** 50996
- **Total questions:** 58112
- **Data sources:** 9

## Modalities

The dataset includes the following medical imaging modalities:

Clinical, Dermatology, Endoscopy, Mammography, Microscopy, Retinography, Ultrasound, Xray

## Tasks

The dataset supports the following tasks:

Classification, Counting, Detection, Multi-label Classification, Regression, Report_Generation


## Dataset Overview

| Dataset | Modality | Images | Tasks | Questions | Sources |
|---------|----------|--------|-------|-----------|---------|
| Dermatology_bcn20000 | Dermatology | 12413 | Classification | 3576 | https://doi.org/10.6084/m9.figshare.24140028.v1 |
| Xray_IUXRay | Xray | 5908 | Report_Generation | 9742 | https://doi.org/10.1093/jamia/ocv080 |
| Ultrasound_iugc | Ultrasound | 5125 | Classification, Detection, Regression | 13302 | https://codalab.lisn.upsaclay.fr/competitions/18413 |
| Xray_chestdr | Xray | 4848 | Classification, Multi-label Classification | 4848 | https://doi.org/10.6084/m9.figshare.c.6476047.v1 |
| Endoscopy_endo | Endoscopy | 3865 | Classification | 80 | https://doi.org/10.6084/m9.figshare.c.6476047.v1 |
| Mammography_CMMD | Mammography | 3582 | Classification | 4493 | https://doi.org/10.7937/tcia.eqde-4b16 |
| Xray_periapical | Xray | 2317 | Classification, Multi-label Classification | 4656 | Private |
| Clinical_neojaundice | Clinical | 2235 | Classification | 745 | https://doi.org/10.6084/m9.figshare.c.6476047.v1 |
| Microscopy_chromosome | Microscopy | 1785 | instance_detection | 1785 | Private |
| Retinography_retino | Retinography | 1392 | Classification | 1392 | https://doi.org/10.6084/m9.figshare.c.6476047.v1 |
| Microscopy_neurips22cell | Microscopy | 1100 | Counting | 1100 | N/A |
| Microscopy_bone_marrow | Microscopy | 1045 | classification | 1045 | PRIVATE |
| Xray_boneresorption | Xray | 1004 | regression | 1004 | PRIVATE |
| Xray_dental | Xray | 1001 | Classification | 5998 | Private |
| Retinography_fundus | Retinography | 987 | Classification | 1974 | Private |
| Ultrasound_BUSI | Ultrasound | 780 | classification | 780 | https://doi.org/10.1016/j.dib.2019.104863 |
| Ultrasound_BUS-UCLM | Ultrasound | 682 | classification | 682 | https://doi.org/10.1038/s41597-025-04562-3 |
| Ultrasound_BUSI-det | Ultrasound | 647 | detection | 647 | https://doi.org/10.1016/j.dib.2019.104863 |
| Ultrasound_BUS-UCLM-det | Ultrasound | 263 | detection | 263 | https://doi.org/10.1038/s41597-025-04562-3 |

**Note:** The numbers shown in the above table include data from all subsets: training, validation-public, validation-hidden, and testing.

## Directory Structure

Each dataset typically follows this structure:

```
modality/
└── dataset_name/
    ├── images[Tr|Val|Ts]/
    │   └── image_files.png
    └── dataset_questions_[train|val].json
```

## Question Format

Questions are formatted as JSON arrays with the following structure:

```json
[
    {
        "TaskType": "Classification",
        "Modality": "X-ray",
        "ImageName": "imagesTr/image001.png",
        "Question": "What abnormality is visible in this image?",
        "Answer": "Fracture",
        "Split": "train"
    }
]
```