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Published on: November 8, 2012
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Surface Foliation Based Brain Morphometry Analysis
Chengfeng Wen1, Na Lei2, Ming Ma1
1Department of Computer Science, Stony Brook University, Stony Brook, NY 11794, USA.
Summary
This study introduces a new brain surface analysis method using surface foliation theory. This approach effectively distinguishes Alzheimer's disease patients from healthy controls using intrinsic geometric features.
Area of Science:
- Neuroimaging
- Computational Geometry
- Medical Image Analysis
Background:
- Brain morphometry is crucial for understanding neurological conditions.
- Current methods may lack intrinsic geometric features for robust analysis.
- Surface foliation theory offers a novel geometric framework.
Purpose of the Study:
- To develop a novel brain surface morphometry analysis method using surface foliation theory.
- To extract intrinsic and informative geometric features from cortical surfaces.
- To evaluate the method's efficacy in classifying Alzheimer's disease patients.
Main Methods:
- Constructing finite foliations on brain cortical surfaces with landmark curves.
- Utilizing Strebel differentials and harmonic maps for surface decomposition.
- Mapping topological cylinders to standard cylinders to extract height and circumference parameters.
Main Results:
- Novel intrinsic surface features were successfully computed.
- The method demonstrated rigorous, geometric, and automatic analysis.
- Experimental classification between Alzheimer's disease and healthy controls showed high efficacy.
Conclusions:
- Surface foliation theory provides a powerful new tool for brain morphometry.
- The proposed features are intrinsic, informative, and geometrically rigorous.
- The method shows significant potential for clinical applications in neurodegenerative disease research.
