Name
Title | ||
|---|---|---|
Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging and neurodegenerative disease modeling. |
Abstract | ||
|---|---|---|
This paper describes a new neuroimaging analysis toolbox that allows for the modeling of nonlinear effects at the voxel level, overcoming limitations of methods based on linear models like the GLM. We illustrate its features using a relevant example in which distinct nonlinear trajectories of Alzheimeru0027s disease related brain atrophy patterns were found across the full biological spectrum of the disease. |
Year | Venue | Field |
|---|---|---|
2016 | arXiv: Machine Learning | Voxel,Nonlinear system,Linear model,Toolbox,Nonlinear regression,Artificial intelligence,Neuroimaging,Mathematics,Machine learning |
DocType | Volume | Citations |
Journal | abs/1612.00667 | 0 |
PageRank | References | Authors |
0.34 | 0 | 11 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Santi Puch | 1 | 0 | 0.34 |
| Asier Aduriz | 2 | 0 | 0.34 |
| Adria Casamitjana | 3 | 9 | 2.54 |
| Veronica Vilaplana | 4 | 133 | 18.07 |
| Paula Petrone | 5 | 0 | 0.68 |
| Grégory Operto | 6 | 0 | 0.34 |
| Raffaele Cacciaglia | 7 | 0 | 0.34 |
| Stavros Skouras | 8 | 6 | 1.58 |
| carles falcon | 9 | 3 | 0.82 |
| José Luis Molinuevo | 10 | 0 | 0.68 |
| Juan D Gispert | 11 | 8 | 2.96 |