The University of Southampton
University of Southampton Institutional Repository

A spatially constrained low-rank matrix factorization for the functional parcellation of the brain

Record type: Article

We propose a new matrix recovery framework to partition brain activity using time series of resting-state functional Magnetic Resonance Imaging (fMRI). Spatial clusters are obtained with a new low-rank factorization algorithm that offers the ability to add different types of constraints. As an example we add a total variation type cost function in order to exploit neighborhood constraints.
We first validate the performance of our algorithm on sim- ulated data, which allows us to show that the neighborhood constraint improves the recovery in noisy or undersampled set-ups. Then we conduct experiments on real-world data, where we simulated an accelerated acquisition by randomly undersampling the time series. The obtained parcellation are reproducible when analysing data from different sets of indi- viduals, and the estimation is robust to undersampling.

PDF BBS14.pdf - Other
Download (640kB)

Citation

Benichoux, A. and Blumensath, T. (2014) A spatially constrained low-rank matrix factorization for the functional parcellation of the brain Proc. 22nd European Signal Processing Conference, pp. 1-5.

More information

Submitted date: 1 September 2014
Published date: October 2014
Organisations: Signal Processing & Control Grp

Identifiers

Local EPrints ID: 363425
URI: http://eprints.soton.ac.uk/id/eprint/363425
PURE UUID: c68323f6-4f6d-4fa1-9d9e-9f4ff9a14760

Catalogue record

Date deposited: 25 Mar 2014 11:50
Last modified: 18 Jul 2017 02:40

Export record

Contributors

Author: A. Benichoux
Author: T. Blumensath

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×