DocumentCode
745248
Title
Myocardial motion analysis from B-mode echocardiograms
Author
Suhling, Michael ; Arigovindan, Muthuvel ; Jansen, Christian ; Hunziker, Patrick ; Unser, Michael
Author_Institution
Biomed. Imaging Group, Swiss Fed. Inst. of Technol. Lausanne, Switzerland
Volume
14
Issue
4
fYear
2005
fDate
4/1/2005 12:00:00 AM
Firstpage
525
Lastpage
536
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 multiresolution 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.
Keywords
echocardiography; image resolution; image sequences; least squares approximations; medical image processing; motion estimation; parameter estimation; wavelet transforms; B-mode echocardiograms; B-spline-weighted inner product computing; cardiac motion quantitative assessment; coarse-to-fine multiresolution framework; heart motion estimation; in vivo echocardiogram; least-square estimation; local-affine model; motion estimation; myocardial contractility; myocardial disfunction; myocardial motion analysis; optical-flow-based method; parameter estimation; sliding spatiotemporal B-spline window; two-dimensional echocardiographic sequence; ultrasound sequence; ventricular malfunction; wavelet-like algorithm; Adaptive optics; Heart; Image analysis; Image motion analysis; Motion analysis; Motion estimation; Myocardium; Optical sensors; Parameter estimation; Spatiotemporal phenomena; Echocardiography; motion estimation; time-varying deformable model; Algorithms; Animals; Artificial Intelligence; Computer Simulation; Dogs; Echocardiography; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Cardiovascular; Movement; Myocardial Infarction; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Phantoms, Imaging; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2004.838709
Filename
1407980
Link To Document