[G-Stats Seminar] Sarang Joshi

Sarang Joshi

The University of Utha

17/11/2021 – h. 4 p.m.

Bio: Before joining SCI, Dr. Joshi was an Assistant Professor of Radiation Oncology and an Adjunct Assistant Professor of Computer Science at the University of North Carolina in Chapel Hill. Prior to joining Chapel Hill Dr. Joshi was Director of Technology Development at IntellX. Sarang’s research interests are in the emerging field of Computational Anatomy and have recently focused on its application to Radiation Oncology.

Title: Integrated Construction of Multimodal Atlases with Structural Connectomes in the Space of Riemannian Metrics

Abstract: The structural network of the brain, or structural connectome, can be represented by fiber bundles generated by a variety of tractography methods. While such methods give qualitative insights into brain structure, there is controversy over whether they can provide quantitative information, especially at the population level. In order to enable population-level statistical analysis of the structural connectome, we propose representing a connectome as a Riemannian metric, which is a point on an infinite-dimensional manifold. We equip this manifold with the Ebin metric, a natural metric structure for this space, to get a Riemannian manifold along with its associated geometric properties. We then use this Riemannian framework to apply object-oriented statistical analysis to define an atlas as the Fr\’echet mean of a population of Riemannian metrics. This formulation ties into the existing framework for diffeomorphic construction of image atlases, allowing us to construct a multimodal atlas by simultaneously integrating complementary white matter structure details from DWMRI and cortical details from T1-weighted MRI. We illustrate our framework with 2D data examples of connectome registration and atlas formation. Finally, we build an example 3D multimodal atlas using T1 images and connectomes derived from diffusion tensors estimated from a subset of subjects from the Human Connectome Project.

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