Name
Abstract | ||
|---|---|---|
We propose a number of source models that are spatially distributed on a line for magnetoencephalography (MEG) using both a spherical head with radial sensors for more efficient computation and a realistic head model for more accurate results. We develop these models with increasing degrees of freedom, derive forward solutions, maximum-likelihood (ML) estimates, and Crame/spl acute/r-Rao bound (CR... |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/TBME.2005.844276 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Magnetoencephalography,Brain modeling,Electroencephalography,Magnetic heads,Maximum likelihood estimation,Epilepsy,Magnetic sensors,Distributed computing,Computational efficiency,Noninvasive treatment | Line source,Expression (mathematics),Computer science,Source model,Distributed source,Artificial intelligence,Computation,Computer vision,Neurophysiology,Algorithm,Model selection,Magnetoencephalography,Machine learning | Conference |
Volume | Issue | ISSN |
52 | 5 | 0018-9294 |
Citations | PageRank | References |
9 | 1.04 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Imam Samil Yetik | 1 | 154 | 20.93 |
| Arye Nehorai | 2 | 12 | 2.53 |
| C. Muravchik | 3 | 543 | 68.59 |
| Jens Haueisen | 4 | 305 | 53.60 |