Name
Abstract | ||
|---|---|---|
Optical imaging is the video recording of two-dimensional patterns of changes in light reflectance from cortical tissue evoked by Stimulation. We derived a method, called extended spatial decorrelation (ESD), that uses second order statistics in space for separating the intrinsic signals into the stimulus related components and the nonspecific variations. The Performance of ESD on model data is compared to independent component analysis (ICA) algorithms using statistics of 4th and higher order. Robustness against sensor noise is scored. When applied to optical images, ESD separates the stimulus specific signal well from biological noise and artifacts. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1007/978-3-642-59802-9_12 | DAGM-Symposium |
Keywords | Field | DocType |
optical imaging data,blind signal separation,optical imaging | Video recording,Computer vision,Decorrelation,Computer science,Robustness (computer science),Independent component analysis,Artificial intelligence,Stimulus (physiology),Blind signal separation,Optical imaging,Light reflectance | Conference |
ISBN | Citations | PageRank |
3-540-67886-7 | 0 | 0.34 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ingo Schiessl | 1 | 28 | 5.76 |
| holger sch oner | 2 | 4 | 1.25 |
| John E. W. Mayhew | 3 | 233 | 322.10 |
| Niall McLoughlin | 4 | 9 | 2.51 |
| Jennifer S. Lund | 5 | 0 | 0.34 |
| Klaus Obermayer | 6 | 1957 | 426.59 |