Name
Title | ||
|---|---|---|
Manifold learning characterization of abnormal myocardial motion patterns: application to CRT-Induced changes |
Abstract | ||
|---|---|---|
The present paper aims at quantifying the evolution of a given motion pattern under cardiac resynchronization therapy (CRT). It builds upon techniques for population-based cardiac motion quantification (statistical atlases, for inter-sequence spatiotemporal alignment and the definition of normal/abnormal motion). Manifold learning is used on spatiotemporal maps of myocardial motion abnormalities to represent a given abnormal pattern and to compare any individual to that pattern. The methodology was applied to 2D echocardiographic sequences in a 4-chamber view from 108 subjects (21 healthy volunteers and 87 CRT candidates) at baseline, with pacing ON, and at 12 months follow-up. Experiments confirmed that recovery of a normal motion pattern is a necessary but not sufficient condition for CRT response. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-38899-6_53 | FIMH |
Keywords | Field | DocType |
inter-sequence spatiotemporal alignment,population-based cardiac motion quantification,abnormal pattern,abnormal motion,abnormal myocardial motion pattern,cardiac resynchronization therapy,crt candidate,myocardial motion abnormality,motion pattern,crt response,crt-induced change,normal motion pattern | Population,Computer vision,Artificial intelligence,Nonlinear dimensionality reduction,Cardiac motion,Cardiac resynchronization therapy,Mathematics | Conference |
Volume | ISSN | Citations |
7945 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 6 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| N Duchateau | 1 | 199 | 20.53 |
| G Piella | 2 | 366 | 43.86 |
| Adelina Doltra | 3 | 103 | 6.15 |
| Lluis Mont | 4 | 5 | 2.24 |
| Josep Brugada | 5 | 73 | 6.06 |
| Marta Sitges | 6 | 132 | 12.62 |
| Bart H. Bijnens | 7 | 164 | 27.56 |
| M De Craene | 8 | 411 | 41.85 |