Name
Title | ||
|---|---|---|
Tetrahedral spectral feature-Based bayesian manifold learning for grey matter morphometry: Findings from the Alzheimer’s disease neuroimaging initiative |
Abstract | ||
|---|---|---|
•A systematic cortical morphometry analysis on three-dimensional manifold.•Explicit weak-form formulations for Laplace-Beltrami and Hamiltonian operators.•Solving heat equation and Schrȵdinger’s equation for tetrahedral spectral analysis.•A novel morphometric Gaussian process regression framework for landmarking.•A series of AD diagnosis experiments and visualizations in the ADNI cohort. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.media.2021.102123 | Medical Image Analysis |
Keywords | DocType | Volume |
Magnetic resonance imaging (MRI),Alzheimer’S disease,Tetrahedral mesh,Spectral shape analysis,Bayesian manifold learning | Journal | 72 |
ISSN | Citations | PageRank |
1361-8415 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yonghui Fan | 1 | 3 | 2.11 |
| Gang Wang | 2 | 0 | 0.34 |
| Qunxi Dong | 3 | 0 | 2.03 |
| Yuxiang Liu | 4 | 0 | 0.34 |
| Natasha Leporé | 5 | 0 | 0.34 |
| Yalin Wang | 6 | 1042 | 79.53 |