Name
Title | ||
|---|---|---|
Cardiac Motion Evolution Model for Analysis of Functional Changes Using Tensor Decomposition and Cross-Sectional Data. |
Abstract | ||
|---|---|---|
Cardiac disease can reduce the ability of the ventricles to function well enough to sustain long-term pumping efficiency. Recent advances in cardiac motion tracking have led to improvements in the analysis of cardiac function. We propose a method to study cohort effects related to age with respect to cardiac function. The proposed approach makes use of a recent method for describing cardiac motion... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TBME.2018.2816519 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Tensile stress,Cardiac disease,Heart,Motion tracking,Analytical models,Image registration,Spatiotemporal phenomena | Population,Computer vision,Tensor,Parametrization,Computer science,Partial least squares regression,Cross-sectional data,Algorithm,Stress (mechanics),Artificial intelligence,Cardiac motion,Cardiac function curve | Journal |
Volume | Issue | ISSN |
65 | 12 | 0018-9294 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kristin McLeod | 1 | 97 | 10.68 |
| Kristin Tøndel | 2 | 19 | 3.26 |
| Lilian Calvet | 3 | 6 | 2.38 |
| Maxime Sermesant | 4 | 1111 | 122.97 |
| Xavier Pennec | 5 | 5021 | 357.08 |