Emory University

University of Miami

Saumya Gurbani

Hyunsuk Shim

Lee Cooper

Sulaiman Sheriff

Andrew Maudsley

Systems and methods provide a parallelized deep learning approach to spectral fitting for magnetic resonance spectroscopy data enabling accurate and rapid spectral fitting and determination of metabolite measurements using a conventional computer. The method may include processing multi-spectra magnetic resonance (MR) spectroscopy data of a region of interest through a series of neural networks. The method may include determining baseline components of each spectrum using a first neural network of the series, generating baseline-corrected components for each spectrum using the baseline components; and determining one or more peak components of each spectrum using a second neural network of the series and the baseline-corrected components. The method may further include determining one or more metabolite measurements of the one or more metabolites in the region of interest using the one or more peak components.

Growing community of inventors

Atlanta, GA, United States of America

Saumya Gurbani