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

Structural MRI data comes in the form of 2D images of axial cross-sections of the brain. MR RF-sequences are designed to generate contrast between different tissues in the brain. Most commonly, T1-weighted images are acquired, showing good contrast between the white matter and the gray matter. Through collaboration with the Psychology department, we were given access to MRI scans of 10 different healthy subjects. This data was first pre-processed using FreeSurfer - a freely available software offering a set of tools for analysis and visualization of brain imaging data. Among the available tools, FreeSurfer provides segmentation of white matter from the rest of the brain, skull stripping, registration of the cortical surface of an individual with an atlas, labeling and segmenting the various regions of the cortical surface. The output of this pre-processing step was a set of 35 cortical segments per subject.

2.Diffusion MRI + Tractography data

Diffusion MRI is an inherently different MR imaging technique which allows mapping the diffusion process of molecules, mainly water, in biological tissues. Molecular diffusion patterns in tissues reflects interactions with macromolecules, fibers, membranes, etc. Water molecule diffusion patterns can therefore reveal microscopic details about tissue architecture, either normal or in a diseased state [cite Wikipedia]. The structure of the neuronal axons of white matter in the brain causes anisotropy in water diffusion in these structures: water will diffuse more rapidly in the direction aligned with the internal structure, and more slowly as it moves perpendicular to the preferred direction. For more details regarding this technique the reader is referred to [].

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.