Name
Abstract | ||
|---|---|---|
The quantitative assessment of cardiac motion is a fundamental concept to evaluate ventricular malfunction. We present a new optical-flow-based method for estimating heart motion from two-dimensional echocardiographic sequences. To account for typical heart motions, such as contraction/expansion and shear, we analyze the images locally by using a local-affine model for the velocity in space and a linear model in time. The regional motion parameters are estimated in the least-squares sense inside a sliding spatiotemporal B-spline window. Robustness and spatial adaptability is achieved by estimating the model parameters at multiple scales within a coarse-to-fine multiresoluion framework. We use a wavelet-like algorithm for computing B-spline-weighted inner products and moments at dyadic scales to increase computational efficiency. In order to characterize myocardial contractility and to simplify the detection of myocardial dysfunction, the radial component of the velocity with respect to a reference point is color coded and visualized inside a time-varying region of interest. The algorithm was first validated on synthetic data sets that simulate a beating heart with a speckle-like appearance of echocardiograms. The ability to estimate motion from real ultrasound sequences was demonstrated by a rotating phantom experiment. The method was also applied to a set of in vivo echocardiograms from an animal study. Motion estimation results were in good agreement with the expert echocardiographic reading. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/TIP.2004.838709 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
typical heart motion,linear model,b-mode echocardiograms,motion estimation result,regional motion parameter,expert echocardiographic reading,heart motion,cardiac motion,beating heart,motion estimation,model parameter,index terms—echocardiography,myocardial motion analysis,time- varying deformable model.,local-affine model,adaptive optics,myocardial contractility,inner product,movement,ultrasound,algorithms,myocardial infarction,image resolution,wavelet transforms,heart,indexing terms,region of interest,synthetic data,animal studies,computer simulation,least square,parameter estimation,least square estimation,image analysis,artificial intelligence,optical flow | Computer vision,Imaging phantom,Multiresolution analysis,Robustness (computer science),Artificial intelligence,Motion analysis,Motion estimation,Region of interest,Estimation theory,Optical flow,Mathematics | Journal |
Volume | Issue | ISSN |
14 | 4 | 1057-7149 |
Citations | PageRank | References |
47 | 2.64 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Sühling | 1 | 109 | 17.77 |
| Muthuvel Arigovindan | 2 | 128 | 17.90 |
| Christian Jansen | 3 | 47 | 2.64 |
| Patrick Hunziker | 4 | 79 | 5.07 |
| Unser, M. | 5 | 3438 | 442.40 |