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Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Updated: Jun 19, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

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

Shanshan Wang^1,2, Shoujun Yu^3,4, 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

This summary is machine-generated.

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.

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Last Updated: Jun 19, 2026

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

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Published on: September 12, 2011

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

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Published on: May 10, 2012

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

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.