Published June 2, 2023
| Version 1.6
Dataset
Open
M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research [V1.6]
Creators
- 1. Shenzhen Technology University
- 2. Jinan University
- 3. Shenzhen Samii Medical Center
- 4. the University of Hong Kong
Description
V1.6 release notes:
- The test subset is released, which contains T1w (6 repetitions/subject), T2w (6 repetitions/subject), and FLAIR (4 repetitions/subject) data from 25 new subjects. These data have passed motion inspection, but one should note that due to the doubled repetition numbers, the average inter-contrast motions are around twice larger than those in the training and validation subsets. To facilitate users, we release the ground truth images as well, but please do not use them during hyperparameter tuning.
V1.5 release notes:
- T1w Gradient echo (GRE) data for all 183 subjects are released. Note that the phase encoding direction for GRE data is in the AP direction, different from other contrasts. These GRE data were not checked for motions.
- A few incorrect records of patient_id were corrected in the H5 files.
- Scans 2022062708 and 2022062709 were removed due to duplication. Two new scans were added to replace them.
V1.1 release notes:
- Please refer to https://www.nature.com/articles/s41597-023-02181-4 for details.
Files
M4Raw_multicoil_test.zip
Files
(27.9 GB)
Name | Size | Download all |
---|---|---|
md5:fb2ff6b684493f122cad4a5f84cba82e
|
5.0 GB | Preview Download |
md5:273862726a714a9b06225b68d56a0374
|
4.8 GB | Preview Download |
md5:8c9335a05e0ad5e0c3030d327cb0110d
|
2.5 GB | Preview Download |
md5:b26afbb2acca8c2dea91b94735b9a94a
|
12.7 GB | Preview Download |
md5:4768c897750b903c98b95dcd79284f7b
|
3.0 GB | Preview Download |
Additional details
Related works
- Is supplemented by
- Software: https://github.com/mylyu/M4Raw (URL)
References
- 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