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Updated: Jun 13, 2026

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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Tensor-based morphometry of fibrous structures with application to human brain white matter
Hui Zhang1, Paul A Yushkevich, Daniel Rueckert
1Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, USA.
Summary
This study introduces advanced tensor-based morphometry (TBM) to analyze shape changes in fibrous structures like brain white matter. The new method quantifies local changes in fiber length and bundle thickness for deeper anatomical insights.
Area of Science:
- Neuroimaging
- Computational Anatomy
- Biomedical Engineering
Background:
- Tensor-based morphometry (TBM) is established for analyzing anatomical shape changes.
- Standard TBM primarily quantifies local volumetric alterations.
Purpose of the Study:
- To extend TBM for detailed shape analysis of fibrous structures.
- To develop intuitive descriptors for local changes in fiber length and thickness.
Main Methods:
- Leveraging diffusion tensor imaging (DTI) data for spatial configuration of fibrous structures.
- Integrating DTI information with spatial transformations from image registration.
- Quantifying fibrous structure-specific changes, including fiber length and bundle thickness.
Main Results:
- The proposed TBM approach provides rich descriptors for shape changes in fibrous tissues.
- Demonstrated application to brain white matter reveals enhanced analytical capabilities.
- The method successfully quantifies local variations in fiber morphology.
Conclusions:
- The extended TBM framework offers novel insights into the structural integrity of fibrous tissues.
- This approach enhances the understanding of anatomical variations in populations and over time.
- The method is particularly valuable for studying complex fibrous structures like brain white matter.

