Name
Title | ||
|---|---|---|
Tensor decomposition processes for interpolation of diffusion magnetic resonance imaging. |
Abstract | ||
|---|---|---|
•A Novel probabilistic framework for interpolation of dMRI-HOT is proposed.•The framework is based on Gaussian processes combined with tensor decompositions.•Results demonstrate improvements in accuracy and generalization to any rank.•Validation on synthetic and real data evaluating anisotropy levels and fiber tracts. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2018.10.005 | Expert Systems with Applications |
Keywords | Field | DocType |
Diffusion magnetic resonance imaging,Higher order tensors,Interpolation,Probabilistic models,Tensor decomposition | Data mining,Anisotropy,Tensor,Computer science,Fractional anisotropy,Scalar (physics),Interpolation,Algorithm,Tucker decomposition,Wishart distribution,Tractography | Journal |
Volume | ISSN | Citations |
118 | 0957-4174 | 0 |
PageRank | References | Authors |
0.34 | 17 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hernán Darío Vargas Cardona | 1 | 4 | 3.25 |
| Álvaro Á. Orozco | 2 | 16 | 12.88 |
| Andrés M. Álvarez | 3 | 0 | 0.34 |
| Mauricio A. Álvarez | 4 | 0 | 1.69 |