Scientific Data (Aug 2025)

Diff5T: Benchmarking human brain diffusion MRI with an extensive 5.0 Tesla k-space and spatial dataset

  • Shanshan Wang,
  • Shoujun Yu,
  • Jian Cheng,
  • Sen Jia,
  • Changjun Tie,
  • Jiayu Zhu,
  • Haohao Peng,
  • Yijing Dong,
  • Jianzhong He,
  • Fan Zhang,
  • Yaowen Xing,
  • Xiuqin Jia,
  • Qi Yang,
  • Qiyuan Tian,
  • Hua Guo,
  • Guobin Li,
  • Hairong Zheng

DOI
https://doi.org/10.1038/s41597-025-05640-2
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 11

Abstract

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Abstract Diffusion magnetic resonance imaging (dMRI) provides critical insights into the microstructural and connectional organization of the human brain. However, the availability of high-field, open-access datasets that include raw k-space data for advanced research remains limited. To address this gap, we introduce Diff5T, a first comprehensive 5.0 Tesla diffusion MRI dataset focusing on the human brain. This dataset includes raw k-space data and reconstructed diffusion images, acquired using a variety of imaging protocols. Diff5T is designed to support the development and benchmarking of innovative methods in artifact correction, image reconstruction, image preprocessing, diffusion modelling and tractography. The dataset features a wide range of diffusion parameters, including multiple b-values and gradient directions, allowing extensive research applications in studying human brain microstructure and connectivity. With its emphasis on open accessibility and detailed benchmarks, Diff5T serves as a valuable resource for advancing human brain mapping research using diffusion MRI, fostering reproducibility, and enabling collaboration across the neuroscience and medical imaging communities.