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Open Imaging Index
MRI Brain

M4Raw

M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research

Raw multi-channel brain MRI data (k-space) from a low-field scanner with repeated scans per contrast, built for reconstruction, denoising and parallel imaging research on affordable MRI. 208 healthy volunteers scanned at 0.3 T with repeated T1, T2 and FLAIR.

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Overview

M4Raw is a raw k-space collection of brain MRI acquired on a low-field (0.3 T) whole-body scanner, released by a team led from Shenzhen Technology University. High-field raw datasets such as fastMRI do not capture the signal and noise behaviour of low-field systems, so M4Raw was built to support learning-based reconstruction, denoising and parallel imaging methods for affordable MRI. Every contrast was scanned several times in a row, so single repetitions can serve as noisy inputs and their average as a cleaner target.

Composition

The original release (V1.1, described in the paper) covers 183 healthy volunteers, mostly college students aged 18 to 32, of whom 116 are male and 67 female. Each has three T1w, three T2w and two FLAIR repetitions of 18 axial slices. Volunteers with notable head motion were moved into a separate motion-corrupted subset; the rest were split at random into 128 training and 30 validation subjects (1,024 and 240 files). V1.5 added a T1-weighted gradient echo series with two repetitions for all 183 volunteers. V1.6 added a test subset of 25 new volunteers with six T1w, six T2w and four FLAIR repetitions each, together with the reference images. The current release has 2,230 files from 208 people.

Acquisition

All data come from one Oper-0.3 permanent-magnet scanner (Ningbo Xingaoyi) with a four-channel head coil. Slices are 5 mm thick with a 1 mm gap, with an in-plane resolution of about 0.94 x 1.23 mm. The k-space of every repetition was exported without averaging, shifted to correct left-right off-centering, and stored as HDF5 with an ISMRMRD-style header and a root-sum-of-squares image, in the array layout used by fastMRI.

Annotations

There are no clinical or anatomical labels. Reconstruction targets are the per-repetition root-sum-of-squares images and the averages over repetitions.

Known limitations

  • One scanner model at one field strength, and a young, narrow-age cohort.
  • Images were not defaced; the thick slices cover only the upper half of the head.
  • Age and sex are published only for the original 183 volunteers.
  • The paper gives 26 motion-corrupted subjects in one place and 25 in another; the released files and the creators' later inventory list 25.
  • The test subset has twice as many repetitions, and its inter-contrast motion is about twice as large as in the training and validation subsets.

Cohort

Aggregate numbers from the sources below. Bars are relative to the 208 subjects.

Sex

  • Female 67 37%
  • Male 116 63%

Covers 183 of 208 subjects.

Imaging protocol in Lyu et al. 2023, Scientific Data 10, 264

Condition

Groups can overlap

  • Healthy control 208 100%

Release inventory in M4Raw Brain v1.6 dataset card on Hugging Face (by the first author)

Field strength

  • 0.3 T 208 100%

Release inventory in M4Raw Brain v1.6 dataset card on Hugging Face (by the first author)

Age

mean 20.1 ± 1.5, range 18 to 32

No age bins reported.

Imaging protocol in Lyu et al. 2023, Scientific Data 10, 264

Contrast / sequence

Groups can overlap

  • T1-weighted 208 100%
  • T2-weighted 208 100%
  • FLAIR 208 100%

Release inventory in M4Raw Brain v1.6 dataset card on Hugging Face (by the first author)

Split

  • Training 128 62%
  • Validation 30 14%
  • Test 25 12%

Subset partition in Lyu et al. 2023, Scientific Data 10, 264; V1.6 release notes in Zenodo record of M4Raw V1.6 (release notes and files)

Contrast combinations

How many subjects have exactly each set of contrasts.

T1wT2wFLAIRSubjects with exactly this set
208

Release inventory in M4Raw Brain v1.6 dataset card on Hugging Face (by the first author)

License and access

Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer

Access
Open download

Download without an account

Access page

Creative Commons Attribution 4.0 International

Use, share and adapt the data for any purpose, including commercial use, as long as you credit the creators.

Original license text Version read: 4.0 Checked 2026-10-07

What you can do

  • Yes
  • Yes
  • Yes
  • Yes
  • Yes

What you can share

  • Yes
  • Yes
  • Yes

What you must do

  • Yes
  • Share alike No
  • No
  • No
  • Manuscript review No
  • Release code No
  • Return results No
  • Delete after use No

Limits

  • No
  • Location limits No

Citation

Lyu M, Mei L, Huang S, et al. M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research. Sci Data 10, 264 (2023). https://doi.org/10.1038/s41597-023-02181-4

@article{lyu_m4raw_2023,
  title = {{M4Raw}: {A} multi-contrast, multi-repetition, multi-channel {MRI} k-space dataset for low-field {MRI} research},
  volume = {10},
  doi = {10.1038/s41597-023-02181-4},
  number = {1},
  journal = {Scientific Data},
  author = {Lyu, Mengye and Mei, Lifeng and Huang, Shoujin and Liu, Sixing and Li, Yi and Yang, Kexin and Liu, Yilong and Dong, Yu and Dong, Linzheng and Wu, Ed X.},
  year = {2023},
  pages = {264},
}

Sources

Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.