Meeting Banner
Abstract #1607

Applying L+S decomposition to improve sensitivity to dynamic changes in functional MR spectroscopy

Adam Berrington1 and I. Betina Ip2
1Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom, 2Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom


Functional MRS (fMRS) is a powerful technique to measure metabolite responses over time. However, noise and spectral contamination limit the ability to study individual metabolite time-courses. In this work, we propose to model fMRS spectra as a superposition of low-rank (L) and sparse components (S). L+S decomposition resulted in separation of temporally-correlated signal from noise in simulation. In vivo, L+S spectra had higher SNR compared to original data (P=0.007) and the mean glutamate time-course, using L+S spectra, was more strongly correlated to stimulus. L+S decomposition is a promising data-driven method to enhance sensitivity to dynamic changes in fMRS.

This abstract and the presentation materials are available to members only; a login is required.

Join Here