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Non-parametric MRI Brain Atlas for the Polish Population
Damian Borys1,2, Marek Kijonka3, Krzysztof Psiuk-Maksymowicz1,2
1Faculty of Automatic Control, Electronics and Computer Science, Department of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland.
Frontiers in Neuroinformatics
|October 25, 2021
Summary
Non-parametric methods are more accurate for creating brain atlases from MRI data, as brain tissue distributions are not Gaussian. This study developed non-parametric templates for the Polish population, improving brain structure segmentation.
Area of Science:
- Neuroimaging and Brain Mapping
- Medical Statistics
- Population Neuroscience
Background:
- Magnetic resonance imaging (MRI) is crucial for in vivo brain morphology studies.
- Existing brain atlases often rely on parametric statistics, assuming Gaussian distributions.
- Empirical data suggest brain tissue distributions deviate from Gaussian shapes.
Purpose of the Study:
- To verify voxel-wise distributions of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) in a healthy population.
- To construct non-parametric brain templates and tissue probability maps (TPMs) for the Polish population.
- To investigate the influence of sex and age on these brain templates.
Main Methods:
- Analysis of voxel-wise tissue distributions using the Shapiro-Wilk test.
- Generation of non-parametric atlases from 96 healthy Polish individuals using 3-Tesla MRI.
- Comparison of non-parametric and parametric maps using Wilcoxon signed-rank and Kolmogorov-Smirnov tests.
Main Results:
- Brain tissue distributions were confirmed to be skewed and non-Gaussian across all brain structures.
- Significant differences were observed between non-parametric and parametric brain templates (GM, WM, CSF).
- Non-parametric atlases resulted in significantly larger gray matter and smaller cerebrospinal fluid volumes during segmentation.
Conclusions:
- Parametric measures are often uncritically used for population atlases, but may not accurately represent skewed distributions.
- Non-parametric methodology provides a more relevant and universal approach for constructing MRI brain atlases.
- The developed non-parametric templates offer improved spatial representation and segmentation accuracy for the Polish population.
