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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...

Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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Related Experiment Video

Updated: Jun 17, 2026

Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance Imaging-Arterial Spin Labeling

Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance Imaging-Arterial Spin Labeling

Published on: May 31, 2024

fMRI data visualization with BrainBlend and Blender.

Martin Pyka¹, Matthias Hertog, Raul Fernandez

¹Department of Psychiatry, University of Münster, Münster, Germany. martin.pyka@uni-muenster.de

Neuroinformatics

|December 25, 2009

Summary

This summary is machine-generated.

BrainBlend enhances neuroimaging analysis by creating 3D visualizations and animations from functional MRI data. This toolbox integrates with existing software for improved exploration of brain activity and network interactions.

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Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

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Last Updated: Jun 17, 2026

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Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

Published on: October 20, 2023

Area of Science:

Neuroimaging analysis
Computational neuroscience
Medical visualization

Background:

Analyzing anatomical and functional magnetic resonance (MR) images requires effective visualization tools.
Current viewers offer limited 3D rendering and temporal change depiction for blood oxygen level-dependent (BOLD) response.
There is a need for advanced visualization methods to explore complex neuroimaging data.

Purpose of the Study:

To introduce BrainBlend, a novel toolbox for creating 3D visualizations and animations of neuroimaging data.
To enable the use of open-source 3D software (Blender) with neuroimaging data from Statistical Parametric Mapping (SPM).
To improve the exploration of spatial and temporal aspects of functional brain networks.

Main Methods:

BrainBlend generates voxel data files compatible with the open-source 3D software Blender.
The toolbox interfaces with SPM, supporting Analyze and Nifti file formats.
It allows rendering of anatomical, functional, and statistical data as transparent volumetric objects.
Animations are created using time courses from general linear model or independent component analysis, and relative BOLD activations.

Main Results:

BrainBlend facilitates the creation of high-quality 3D images and animations from neuroimaging data.
The software enables time-resolved depiction of hemodynamic changes and BOLD activations.
Animations can be synchronized with paradigm matrices and presented stimuli.
Visual exploration of functional network interactions is significantly enhanced.

Conclusions:

BrainBlend offers a powerful solution for visualizing and exploring complex neuroimaging data in 3D.
The toolbox enhances the understanding of functional network dynamics and temporal BOLD changes.
It meets high visual quality demands for scientific communication in neuroscience.