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2. Permitted Use

The dataset is intended solely for academic, research, and educational purposes.
Any commercial exploitation of the dataset without prior permission is strictly forbidden.
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3. Data Protection and Privacy

Acknowledge the presence of sensitive information within the dataset and commit to maintaining data confidentiality.
Direct attempts to re-identify individuals from the dataset are prohibited.
Ensure compliance with data protection laws such as GDPR and HIPAA.

4. Attribution

Cite the dataset and acknowledge the providers in any publications resulting from its use.
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5. Redistribution

Redistribution of the dataset or any portion thereof is not allowed.
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6. Disclaimer
The dataset is provided "as is" without warranty of any kind, either expressed or implied, including but not limited to the accuracy or completeness of the data.

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8. Access Revocation
Violation of these terms may result in the termination of your access to the dataset.

9. Amendments
The terms and conditions may be updated at any time; continued use of the dataset signifies acceptance of the new terms.

10. Governing Law
These terms are governed by the laws of the location of the dataset providers, excluding conflict of law rules.

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MR-RATE: A Vision-Language Foundation Model and Dataset for Magnetic Resonance Imaging

Paper (Coming soon) | GitHub | Dataset Repositories | Model Weights (Coming soon)

Welcome to the official page for MR-RATE, a pioneering vision-language model and 3D medical imaging dataset that uniquely pairs textual data with brain and spine MRI volumes. Following the approach of CT-RATE, the first 3D medical imaging dataset to pair images with textual reports, MR-RATE offers brain and spine MRI volumes matched with corresponding radiology reports and metadata, all freely accessible to researchers.

A novel dataset of brain and spine MRI volumes with corresponding radiology text reports and metadata

A major challenge in computational research on 3D medical imaging is the lack of comprehensive datasets. Addressing this issue, we present the MR-RATE dataset, consisting of 705,254 non-contrast and contrast-enhanced brain and spine MRI volumes from 98,334 imaging studies of 83,425 unique patients, paired with corresponding radiology text reports and metadata. Brain and spine MRI examinations are acquired from patients using MRI scanners and organised into multiple imaging sequence categories, including T1-weighted, T2-weighted, FLAIR, SWI, and MRA. Each study is paired with associated metadata and a radiology report, which is produced by the radiologist during clinical interpretation. Together, these components constitute the MR-RATE dataset for multimodal brain and spine MRI research.

MRI Volumes and Metadata

All MRI volumes are provided in their native acquisition space. DICOM files are converted to NIfTI format using dcm2niix, as NIfTI is more convenient for research workflows and downstream processing. This conversion also allows DICOM metadata to be selectively curated, removing identifying information while preserving relevant acquisition and study details, which are then saved in CSV format. For each brain volume, a brain mask is predicted using HD-BET, and defacing is then applied using Quickshear to remove identifiable facial features for patient anonymization. The predicted brain masks and defacing masks are released alongside the defaced volumes, enabling researchers to leverage these directly in their own workflows.

In addition to the native-space data, MR-RATE offers three sets of derivatives:

Co-registered volumes — Within each study, a T1-weighted brain MRI is selected to be the center modality, and all the other brain MRI volumes (defined as moving modalities) are registered to the center using ANTs, bringing all brain MRI sequences of a given study into a common anatomical reference frame. Brain mask and defacing mask of center modality are shared accross all modalities of a study.
Atlas-registered volumes — Within each study, the center modality is registered to the MNI152 atlas using ANTs and co-registered moving modalities are also transformed to atlas-space, enabling group-level analyses and cross-patient comparisons in a standardized coordinate space. Brain mask and defacing mask of center modality are also transformed to atlas-space and shared accross all modalities of a study.
Multi-label brain segmentations — Voxel-wise anatomical segmentations are predicted for center modality brain MRI volumes in native space using a foundational segmentation model, supporting region-of-interest analysis and volumetric quantification.

Radiology Reports

All radiology reports are anonymized to remove patient healthcare identifiers, translated into English, and finally re-organized into clinical information, technique, findings and impression sections. Reports are also saved in CSV format.

Data Splits

To support reproducible research, we provide patient-level data splits consisting of 75,000 training, 3,425 validation, and 5,000 test patients. The splits are used internally for our own experiments and are shared openly so that the research community can benchmark and compare methods under consistent conditions.

Dataset Repositories

The MR-RATE dataset is released across four Hugging Face repositories:

Forithmus/MR-RATE (this repo) — Native-space defaced MRI volumes with brain masks and defacing masks, radiology text reports, metadata, and data splits
Forithmus/MR-RATE-coreg — Co-registered MRI volumes (moving modalities registered to the T1-weighted center modality) with brain masks and defacing masks of center modalities
Forithmus/MR-RATE-atlas — Atlas-space MRI volumes (all modalities registered to the MNI152 atlas) with brain masks and defacing masks of center modalities in atlas-space
Forithmus/MR-RATE-seg — Multi-label brain segmentation maps for center modality images in native-space

An interactive Streamlit dashboard is also available for data exploration, enabling cohort filtering and dynamic visualization.

Dataset Guide

A detailed guide explaining the dataset organization, the preprocessing steps used, and download instructions is coming soon.

Citing Us

When using this dataset, please consider citing the following related papers:

Coming soon

Ethical Approval

Information for researchers who require ethical approval documentation for grant applications is coming soon.

License

We are committed to fostering innovation and collaboration in the research community. To this end, all elements of the MR-RATE dataset are released under a Creative Commons Attribution (CC BY-NC-SA 4.0) license. This licensing framework ensures that our contributions can be freely used for non-commercial research purposes, while also encouraging contributions and modifications, provided that the original work is properly cited and any derivative works are shared under similar terms.

For commercial inquiries related to MR-RATE, please contact: contact@forithmus.com.

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