Regularized FOCUSS algorithm for EEG/MEG source imaging

被引：0

作者：

Han, J ^{[1
]}

Park, KS ^{[1
]}

机构：

[1] Seoul Natl Univ, Interdisciplinary Program Biomed Engn, Seoul, South Korea

来源：

PROCEEDINGS OF THE 26TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7 | 2004年 / 26卷

关键词：

dipole; electroencephalography; inverse problem; sparse; regularization;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, we derived a generalized version of the regularized FOCUSS algorithm which was derived in [3]. It allows general forms of noise covariance and reduces depth effect when imaging focal neural sources from electroencephalography (EEG) / magnetoencephalography (MEG) data. We compared a depth-weighted regularized algorithm with FOCUSS and a regularized FOCUSS through simulation study. The suggested algorithm gave sparser and less spurious solutions than the others.

引用

页码：122 / 124

页数：3

共 3 条

[1] Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum norm algorithm
Gorodnitsky, IF
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[2] MEG-based imaging of focal neuronal current sources
Phillips, JW
Leahy, RM
Mosher, JC
[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 1997, 16 (03) : 338 - 348
[3] Subset selection in noise based on diversity measure minimization
Rao, BD
Engan, K
Cotter, SR
Pahner, J
Kreutz-Delgado, K
[J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2003, 51 (03) : 760 - 770

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