Shape Analysis on Neuroimaging Data

Tanya Glozman

Introduction

Understanding the relationships between structure and function in the brain is a key interest in neuroscience. Many studies indicate a correlation between structural/shape abnormalities and functional differences between subjects ranging from behavioral changes through functional differences to neurological disorders - an overview can be found in [3]. However, these studies focus mostly on cortical structures. In this project we explored the efficacy of projections in describing the shape of two types of neuroimaging data: cortical segments acquired from Structural MRI data and white matter fascicles (neuronal tracts) acquired from Diffusion Weighted MRI tractography data. We developed a new descriptor based on projections, and proved it's efficacy on these types of data by performing SVM-based classification of the different structures. We show that our simple descriptor greatly reduces the dimentionality of the problem while preserving fine shape information required to discriminate between different structures.

Data

Two types of neuroimaging data were explored: 1.Structural MRI data 2.Diffusion MRI + Tractography data

Methods

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Results

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Conclusions

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References

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Appendix I

This project is ongoing. The data was acquired through collaboration with Dr. Franco Pestilli (for the connectome data )and Prof. Tony Norcia's group (for the structural MRI data. I am not free to share the data. Since we are hoping to publish the results of this work, we prefer to not share the code currently. Please email tanyagl@stanford.edu if you'd like to learn more.