Study on Deterministic Regularization Approach for Neuromagnetic Source Reconstruction
The Magnetoencephalography (MEG) inverse problem of reconstructing electrical sources in the human brain is indeed ill-posed and largely underdetermined. An efficient way of constraining the problem and thereby reducing the solution space is to perform regularization. Under the distributed source model, a region weighing approach present here is built on the minimum norm with Tikhonov regularization. One weighing matrix is considered from the algorithm feature of MEG equation, whereas another is from the sparse feature of source distribution to form an operator of region weighing so as to yield a satisfied solution.Computer simulations demonstrate this modified method is able to obtain a better source reconstruction.
Ill-posed Deterministic Regularization Region Weighing Reconstruction, Neuromagnetic Source
Jing Hu Shiyan Ying
College of Information Engineering, Zhejiang University of Technology Hangzhou, 310032, China
国际会议
杭州
英文
341-343
2006-10-12（万方平台首次上网日期，不代表论文的发表时间）