DocumentCode :
4533
Title :
Spatially Sparse, Temporally Smooth MEG Via Vector 
Author :
Cassidy, Ben ; Solo, Victor
Author_Institution :
Sch. of Electr. Eng., Univ. of New South Wales, Sydney, NSW, Australia
Volume :
34
Issue :
6
fYear :
2015
fDate :
Jun-15
Firstpage :
1282
Lastpage :
1293
Abstract :
In this paper, we describe a new method for solving the magnetoencephalography inverse problem: temporal vector ℓ0-penalized least squares (TV-L0LS). The method calculates maximally sparse current dipole magnitudes and directions via spatial ℓ0 regularization on a cortically-distributed source grid, while constraining the solution to be smooth with respect to time. We demonstrate the utility of this method on real and simulated data by comparison to existing methods.
Keywords :
inverse problems; least squares approximations; magnetoencephalography; medical signal processing; cortically-distributed source grid; inverse problem; magnetoencephalography; maximally sparse current dipole magnitudes; spatial ℓ0 regularization; spatially sparse temporally smooth MEG; temporal vector ℓ0-penalized least squares; Brain modeling; Data models; Inverse problems; Sensor phenomena and characterization; Tuning; Vectors; Biomedical imaging; encephalography; optimization; sparsity;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2014.2383376
Filename :
7001685
Link To Document :
