Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Correction: Improving tractography in peri-lesional oedema using constrained spherical deconvolution in paediatric neurosurgery patients.

Brain structure & function·2026

Same author

Data-Driven Characterization of Knee Structures Using Non-Negative Matrix Factorization of 3D Multi-Echo UTE MRI.

NMR in biomedicine·2026

Same author

Efficacy of Specific Skilled Motor Versus General Exercise Training on Muscle and Neural Alterations in Recurrent Low Back Pain: Protocol of a Randomized Clinical Trial.

Perceptual and motor skills·2026

Same author

Improving tractography in peri-lesional oedema using constrained spherical deconvolution in paediatric neurosurgery patients.

Brain structure & function·2026

Same author

Did you know? State-of-the-art preprocessing diffusion MRI data can improve tractography.

Brain structure & function·2026

Same author

Combining magnetic resonance imaging and evoked potentials enhances machine learning prediction of multiple sclerosis disability worsening.

Frontiers in immunology·2026

Same journal

Investigating the Neural Origins of Ear-EEG: A Correlation Study Using Scalp EEG Source Reconstruction.

NeuroImage·2026

Same journal

Hysteresis effects in visual and auditory perception and the comparison of underlying neural mechanisms - an EEG study.

NeuroImage·2026

Same journal

Short-term audio-tactile training affects cortical auditory speech-envelope tracking for incongruent but not congruent stimuli.

NeuroImage·2026

Same journal

Dissociable Neurocognitive Mechanisms of State and Trait Anxiety in Working Memory: Threat-Induced Alterations in Decision Dynamics and Attenuation of Large-Scale Network Reconfiguration.

NeuroImage·2026

Same journal

Neuro-Ocular Amyloid Characterization in Alzheimer's Disease via Cross-Site PET-MRI and Hierarchical Cross-Attention Driven Multimodal Representation Learning.

NeuroImage·2026

Same journal

Whole-brain network dynamics underlying intolerance of uncertainty.

NeuroImage·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 26, 2026

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

Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data.

Ben Jeurissen¹, Jacques-Donald Tournier², Thijs Dhollander³

¹iMinds - Vision Lab, Dept. of Physics, University of Antwerp, Belgium; The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia.

|August 12, 2014

Summary

This summary is machine-generated.

Multi-shell, multi-tissue Constrained Spherical Deconvolution (MSMT-CSD) enhances diffusion MRI analysis by accurately mapping white matter, grey matter, and cerebrospinal fluid. This method improves fibre orientation precision and tractography reliability compared to single-shell approaches.

Keywords:

Diffusion MRI Fibre orientation distribution functions Multi-shell acquisition Multiple tissue types Spherical deconvolution Tissue segmentation

More Related Videos

Diffusion Imaging in the Rat Cervical Spinal Cord

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

Related Experiment Videos

Last Updated: Apr 26, 2026

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

Diffusion Imaging in the Rat Cervical Spinal Cord

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Published on: December 9, 2010

Area of Science:

Neuroimaging
Diffusion Magnetic Resonance Imaging (dMRI)
Computational Neuroscience

Background:

Constrained Spherical Deconvolution (CSD) is vital for white matter (WM) tractography in dMRI but traditionally limited to single-shell data.
Existing CSD methods struggle with multi-shell data and accurately characterizing non-white matter tissues like grey matter (GM) and cerebrospinal fluid (CSF).
Limitations include unreliable fibre orientation distribution function (fODF) estimates and overestimation of WM in mixed-tissue voxels.

Purpose of the Study:

To develop and validate a multi-shell, multi-tissue CSD (MSMT-CSD) approach for dMRI.
To leverage b-value dependencies for estimating multi-tissue orientation distribution functions (ODFs).
To compare MSMT-CSD against single-shell, single-tissue CSD (SSST-CSD) for improved accuracy and reliability.

Main Methods:

Incorporation of multi-shell data support into the CSD framework.
Exploitation of distinct tissue-specific b-value responses to estimate multi-tissue ODFs.
Validation using both simulated and real dMRI datasets, comparing MSMT-CSD with SSST-CSD.

Main Results:

MSMT-CSD accurately generates WM/GM/CSF volume fraction maps directly from dMRI data.
SSST-CSD tends to overestimate WM volume in voxels containing GM and/or CSF.
MSMT-CSD significantly enhances fODF orientation precision and reduces spurious peaks in mixed-tissue voxels compared to SSST-CSD.

Conclusions:

MSMT-CSD offers a robust solution for analyzing multi-shell dMRI data across different tissue types.
The method provides more reliable apparent fibre density (AFD) measures and tractography results.
MSMT-CSD represents a significant advancement for quantitative dMRI analysis in neuroscience research.