Name
Abstract | ||
|---|---|---|
Overview of two projects related to determination of in-vivo physiology in the cardiovascular system from magnetic resonance is given. In one instance, we describe a recently developed technique for determining intravascular pressures from MR velocity data which offers advantages over previously proposed approaches. This technique performs harmonics-based orthogonal projection of noisy pressure gradients computed from pulsatile velocity data based on the Navier-Stokes equation onto an integrable subspace and results in a valid dynamic scalar pressure field. In a second instance, an improved framework for estimation of 3-D left-ventricular deformations from tagged MRI is described. Contiguous short- and long-axis tagged MR images are collected and are used within a 4-D B-spline based deformable model to determine 4-D displacements and strains. The framework entails use of both tagged images and 2-D dense displacements obtained from band-pass phase information |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ISBI.2007.356946 | ISBI |
Keywords | Field | DocType |
harmonics-based orthogonal projection,two-dimensional dense displacements,cardiology,medical analysis,band-pass phase information,blood pressure measurement,four-dimensional displacements,four-dimensional strains,magnetic resonance velocity data,integrable subspace,intravascular pressures,pulsatile velocity data,navier-stokes equations,noisy pressure gradients,four-dimensional deformable model,three-dimensional deformations,cardiovascular system,physiological models,biomedical mri,deformation,magnetic resonance,tagged magnetic resonance imaging,dynamic scalar pressure field,left-ventricular deformations,cardiovascular mechanics,medical imaging,splines (mathematics),navier-stokes equation,b-spline based deformable model,tagged mr images,in-vivo physiology,image analysis,spline,physiology,orthogonal projection,band pass,indexing terms,magnetic resonance imaging,pressure gradient | Integrable system,Orthographic projection,Medical imaging,Computer science,Scalar (physics),Harmonics,Artificial intelligence,Pressure gradient,Computer vision,Subspace topology,Algorithm,Classical mechanics,Navier–Stokes equations | Conference |
ISSN | ISBN | Citations |
1945-7928 | 1-4244-0672-2 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amir A. Amini | 1 | 443 | 63.30 |
| Jian Chen | 2 | 0 | 0.34 |
| Yuehuan Wang | 3 | 10 | 4.20 |