Name
Abstract | ||
|---|---|---|
We propose an approach to analyzing functional neuroimages in which (1) regions of neuronal activation are described by a superposition of spatial kernel functions, the parameters of which are estimated from the data and (2) the presence of activation is detected by means of a generalized likelihood ratio test (GLRT). Kernel methods have become a staple of modern machine learning. Herein, we show ... |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TMI.2007.896934 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Bayesian methods,Kernel,Neuroimaging,Biomedical imaging,Testing,Biomedical engineering,Statistical analysis,Machine learning,Computational modeling,Computer science | Radial basis function kernel,Pattern recognition,Kernel embedding of distributions,Computer science,Support vector machine,Artificial intelligence,Relevance vector machine,Overfitting,Kernel method,Variable kernel density estimation,Kernel (statistics) | Journal |
Volume | Issue | ISSN |
26 | 12 | 0278-0062 |
Citations | PageRank | References |
5 | 0.50 | 13 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ana S. Lukic | 1 | 51 | 6.32 |
| Miles N. Wernick | 2 | 595 | 61.13 |
| Dimitris Tzikas | 3 | 248 | 12.95 |
| Xu Chen | 4 | 5 | 0.50 |
| aristidis likas | 5 | 1926 | 140.40 |
| Nikolas P. Galatsanos | 6 | 632 | 52.16 |
| Yongyi Yang | 7 | 1409 | 140.74 |
| E. Zhao | 8 | 5 | 0.50 |
| Stephen C. Strother | 9 | 399 | 56.31 |