Diff5T: Benchmarking Human Brain Diffusion MRI with an Extensive 5.0 Tesla K-Space and Spatial Dataset

TL;DR

Diff5T is a comprehensive open-access 5.0 Tesla diffusion MRI dataset with raw k-space data, designed to facilitate benchmarking and development of advanced brain imaging methods.

Contribution

It introduces the first extensive 5.0 Tesla diffusion MRI dataset with raw data, supporting research in artifact correction, reconstruction, and brain connectivity analysis.

Findings

Provides a large, diverse dataset for method benchmarking

Enables reproducibility in diffusion MRI research

Supports development of advanced imaging techniques

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.