Name
Title | ||
|---|---|---|
Robust extrapolation scheme for fast estimation of 3D ising field partition functions: application to within-subject fMRI data analysis. |
Abstract | ||
|---|---|---|
In this paper, we present a fast numerical scheme to estimate Partition Functions (PF) of 3D Ising fields. Our strategy is applied to the context of the joint detection-estimation of brain activity from functional Magnetic Resonance Imaging (fMRI) data, where the goal is to automatically recover activated regions and estimate region-dependent hemodynamic filters. For any region, a specific binary Markov random field may embody spatial correlation over the hidden states of the voxels by modeling whether they are activated or not. To make this spatial regularization fully adaptive, our approach is first based upon a classical path-sampling method to approximate a small subset of reference PFs corresponding to prespecified regions. Then, the proposed extrapolation method allows us to approximate the PFs associated with the Ising fields defined over the remaining brain regions. In comparison with preexisting approaches, our method is robust to topological inhomogeneities in the definition of the reference regions. As a result, it strongly alleviates the computational burden and makes spatially adaptive regularization of whole brain fMRI datasets feasible. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-04268-3_120 | MICCAI |
Keywords | Field | DocType |
whole brain fmri,within-subject fmri data analysis,remaining brain region,brain activity,classical path-sampling method,spatial regularization,ising field,ising field partition functions,proposed extrapolation method,robust extrapolation scheme,fast estimation,activated region,reference region,spatial correlation,sampling methods,partition function,data analysis | Voxel,Spatial correlation,Partition function (mathematics),Pattern recognition,Markov random field,Computer science,Partition function (statistical mechanics),Extrapolation,Ising model,Regularization (mathematics),Artificial intelligence | Conference |
Volume | Issue | ISSN |
12 | Pt 1 | 0302-9743 |
Citations | PageRank | References |
7 | 0.58 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laurent Risser | 1 | 241 | 18.63 |
| Thomas Vincent | 2 | 320 | 27.52 |
| Philippe Ciuciu | 3 | 452 | 50.82 |
| Idier, J. | 4 | 566 | 59.01 |