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FLARE25 Medical Multimodal Dataset

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

Description

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:

[
    {
        "TaskType": "Classification",
        "Modality": "X-ray",
        "ImageName": "imagesTr/image001.png",
        "Question": "What abnormality is visible in this image?",
        "Answer": "Fracture",
        "Split": "train"
    }
]
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Models trained or fine-tuned on FLARE-MedFM/FLARE-Task5-MLLM-2D