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Brain status modeling with non-negative projective dictionary learning

Authors :
Zhang, M. (Mingli)
Desrosiers, C. (Christian)
Guo, Y. (Yuhong)
Khundrakpam, B. (Budhachandra)
Al-Sharif, N. (Noor)
Kiar, G. (Greg)
Valdes-Sosa, P. (Pedro)
Poline, J.-B. (Jean-Baptiste)
Evans, A. (Alan)
Zhang, M. (Mingli)
Desrosiers, C. (Christian)
Guo, Y. (Yuhong)
Khundrakpam, B. (Budhachandra)
Al-Sharif, N. (Noor)
Kiar, G. (Greg)
Valdes-Sosa, P. (Pedro)
Poline, J.-B. (Jean-Baptiste)
Evans, A. (Alan)
Source :
NeuroImage
Publication Year :
2019

Abstract

Accurate prediction of individuals’ brain age is critical to establish a baseline for normal brain development. This study proposes to model brain development with a novel non-negative projective dictionary learning (NPDL) approach, which learns a discriminative representation of multi-modal neuroimaging data for predicting brain age. Our approach encodes the variability of subjects in different age groups using separate dictionaries, projecting features into a low-dimensional manifold such that information is preserved only for the corresponding age group. The proposed framework improves upon previous discriminative dictionary learning methods by inco

Details

Database :
OAIster
Journal :
NeuroImage
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1156988118
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1016.j.neuroimage.2019.116226