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.
@article{arxiv.2412.06666,
title = {Diff5T: Benchmarking Human Brain Diffusion MRI with an Extensive 5.0 Tesla K-Space and Spatial Dataset},
author = {Shanshan Wang and Shoujun Yu and Jian Cheng and Sen Jia and Changjun Tie and Jiayu Zhu and Haohao Peng and Yijing Dong and Jianzhong He and Fan Zhang and Yaowen Xing and Xiuqin Jia and Qi Yang and Qiyuan Tian and Hua Guo and Guobin Li and Hairong Zheng},
journal= {arXiv preprint arXiv:2412.06666},
year = {2024}
}