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EDEN2020 Human Brain MRI Datasets for Healthy Volunteers

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This dataset provides high-resolution multimodal MRI data from 15 healthy adult volunteers acquired on a 3T scanner at the Neuroradiology Unit and CERMAC (Center of Excellence for High Field Magnetic Resonance), Vita-Salute San Raffaele University, and IRCCS San Raffaele Scientific Institute in Milan, Italy.
The dataset was collected as part of the EDEN2020 (Enhanced Delivery Ecosystem for Neurosurgery on 2020) project, funded by the European Commission (Grant 688279), to advance imaging-guided neurosurgical research.

Each subject’s dataset includes structural, angiographic, and diffusion MRI data for morphological, vascular, and white matter microstructure analysis.
The collection supports research in HARDI, DTI, NODDI, and probabilistic tractography, with derived maps and reconstructions provided in NIfTI-1 format.


License

Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY-NC-ND 4.0)


Citation

Castellano, A., Pieri, V., Galvan, S., Rodriguez y Baena, F., & Falini, A. (2019).
EDEN2020 Human Brain MRI Datasets for Healthy Volunteers (1.0) [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.3994749


Source

https://doi.org/10.5281/zenodo.3994749
Contact: antonella.castellano@hsr.it
Institution: Vita-Salute San Raffaele University / IRCCS San Raffaele Scientific Institute
Project: EDEN2020 — Enhanced Delivery Ecosystem for Neurosurgery on 2020
Funding: European Commission, Horizon 2020 (Grant No. 688279)


Dataset Information

Category Details
Subjects 15 healthy adult volunteers
Scanner 3T MRI scanner (CERMAC, Milan, Italy)
Sequences Included T1_3D_PROSET_Sag, 3D_FLAIR_Tra, SWIp_axial, s3DI_MC_HR, MIP_s3DI_MC_HR, raw_data_DTI_32, raw_data_NODDI, B0_reverse
Derived Data DTI maps, HARDI maps, NODDI maps, probabilistic tractography
File Format NIfTI-1 (.nii, .nii.gz)
Data Conversion DICOM converted using dcm2niix v1.0.20200331
Institutions Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute
Location Milan, Italy

Purpose

The EDEN2020 Human Brain MRI Dataset was created to establish a multimodal imaging reference for neurosurgical navigation and tractography validation.
By integrating high-resolution anatomical, angiographic, and diffusion imaging, the dataset enables quantitative modeling of gray–white matter boundaries, vascular structures, and fiber connectivity.
It provides essential test data for developing and benchmarking tools in neuro-navigation, white matter modeling, and advanced diffusion reconstruction.


File Information

File Description Size Checksum
CTRL_0866.zip MRI data of subject 0866 491.5 MB md5:df3d0c1861c71fb7830044e2170e4f91
CTRL_0933.zip MRI data of subject 0933 431.7 MB md5:7aa43fd122fa8fd3a216b01ceca05e24
CTRL_1277.zip MRI data of subject 1277 480.5 MB md5:82a3858df7ff6dbafa34f053b515983c
CTRL_1686.zip MRI data of subject 1686 446.3 MB md5:6b6d8e21596ec1286e4f6dbe2f6f823f
CTRL_2020.zip MRI data of subject 2020 451.1 MB md5:eced02b3490f1aa88013d1a306a0bb33
CTRL_2476.zip MRI data of subject 2476 440.5 MB md5:4d5c95bb775e436beceb0a096e4c608f
CTRL_3352.zip MRI data of subject 3352 456.0 MB md5:f160d356f3a10247bd6976105ca6ebd4
CTRL_4871.zip MRI data of subject 4871 509.1 MB md5:47bf407fc8eff932b320f4925c999ccc
CTRL_5069.zip MRI data of subject 5069 545.4 MB md5:e49e6e22bc06f80cb28ac547736dbf84
CTRL_5361.zip MRI data of subject 5361 404.6 MB md5:53c7e8690d1536c2e1f2cd98608dac2a
CTRL_5900.zip MRI data of subject 5900 436.2 MB md5:8f16a811a387159862b596bd1304c09c
CTRL_5960.zip MRI data of subject 5960 436.6 MB md5:de6226940f7ce947cdda06c400990e22
CTRL_6685.zip MRI data of subject 6685 443.7 MB md5:379dc0a1cf20c57a3f2b502b7abfede8
CTRL_8275.zip MRI data of subject 8275 481.1 MB md5:84f06997887050241175b3a5489f9f77
CTRL_9647.zip MRI data of subject 9647 467.7 MB md5:b0956d2f7cf93528e04d7901f31eeb55
Readme.md Original dataset documentation 4.6 KB md5:7681547ae40a72b7d43301dd31c6a371

Keywords

MRI • HARDI • DTI • NODDI • Tractography • Brain • Neurosurgery • White Matter • High-Resolution MRI • EDEN2020