A joint network optimization framework to predict clinical severity from resting state functional MRI data

A joint network optimization framework to predict clinical severity from resting state functional MRI data

We propose a novel optimization framework to predict clinical severity from resting state fMRI (rs-fMRI) data. Our model consists of two coupled terms. The first term decomposes the correlation matrices into a sparse set of representative subnetworks that define a network manifold. These subnetworks...

Full description

Bibliographic Details
Main Authors: N.S. D’Souza, M.B. Nebel, N. Wymbs, S.H. Mostofsky, A. Venkataraman
Format: Article
Language:English
Published: Elsevier 2020-02-01
Series:NeuroImage
Subjects:
Matrix factorization
Dictionary learning
Functional magnetic resonance imaging
Clinical severity
Online Access:http://www.sciencedirect.com/science/article/pii/S105381191930905X

Internet

http://www.sciencedirect.com/science/article/pii/S105381191930905X

Similar Items