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Diff5T: Benchmarking human brain diffusion MRI with an extensive 5.0 Tesla k-space and spatial dataset.
Shanshan Wang1,2, Shoujun Yu3,4, Jian Cheng5
1Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. ss.wang@siat.ac.cn.
Scientific Data
|August 4, 2025
Summary
Introducing Diff5T, a comprehensive 5.0 Tesla diffusion MRI dataset for human brain research. This open-access resource provides raw k-space data to advance neuroimaging methods and brain mapping.
Area of Science:
- Neuroimaging
- Human Brain Mapping
- Diffusion MRI
Background:
- Diffusion MRI (dMRI) is crucial for understanding brain microstructure and connectivity.
- Limited availability of high-field, open-access dMRI datasets with raw k-space data hinders advanced research.
Purpose of the Study:
- To introduce Diff5T, the first comprehensive 5.0 Tesla dMRI dataset for the human brain.
- To provide raw k-space data and reconstructed images to support method development and benchmarking.
Main Methods:
- Acquisition of a 5.0 Tesla dMRI dataset with diverse imaging protocols.
- Inclusion of raw k-space data and reconstructed diffusion images.
- Detailed characterization of diffusion parameters, including multiple b-values and gradient directions.
Main Results:
- Creation of the Diff5T dataset, a valuable resource for the scientific community.
- The dataset supports research in artifact correction, image reconstruction, and diffusion modeling.
- Facilitates advanced tractography and analysis of human brain microstructure and connectivity.
Conclusions:
- Diff5T addresses the need for high-quality, open-access dMRI data.
- It serves as a benchmark for developing and validating novel neuroimaging techniques.
- Promotes reproducibility and collaboration in neuroscience and medical imaging research.
