# Structural Connectome Atlas Construction in the Space of Riemannian Metrics

arXiv: https://arxiv.org/abs/2103.05730 · HTML: https://mlsanity.com/paper/2103.05730/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 26 references that are in the map.
- First posted on arXiv 9 Mar 2021.

## Builds on (most cited first, 1 of 1)

- [Diffeomorphic density matching by optimal information transport](https://mlsanity.com/paper/1501.07635/) (2015)

## Built on by (most cited first, 2 of 2)

- [Modeling the Shape of the Brain Connectome via Deep Neural Networks](https://mlsanity.com/paper/2203.06122/) (2022)
- [Integrated Construction of Multimodal Atlases with Structural Connectomes in the Space of Riemannian Metrics](https://mlsanity.com/paper/2109.09808/) (2021)

## Abstract (arXiv)

The structural connectome is often represented by fiber bundles generated from various types of tractography. We propose a method of analyzing connectomes by representing them as a Riemannian metric, thereby viewing them as points in an infinite-dimensional manifold. After equipping this space with a natural metric structure, the Ebin metric, we apply object-oriented statistical analysis to define an atlas as the Fr'echet mean of a population of Riemannian metrics. We demonstrate connectome registration and atlas formation using connectomes derived from diffusion tensors estimated from a subset of subjects from the Human Connectome Project.