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Myocardial Motion Estimation from Echocardiograms

Investigator: Michael Sühling

Summary: We have developed a novel optical-flow-based algorithm to estimate ventricular wall motion from B-mode echocardiograms. The technique uses a local affine model of the deformation and gives access to local strain-rate parameters.

Introduction

Echocardiography is a widely used imaging technique to examine myocardial function in patients with known or suspected heart disease. The analysis of ventricular wall motion and deformation, in particular, allows one to assess the extent of myocardial ischemia and infarction. In clinical practice, the analysis relies mainly on visual inspection or on manual measurements by experienced cardiologists. Manual methods are tedious and time-consuming, and visual assessment leads to qualitative and subjective diagnoses that suffer from considerable inter- and intraobserver variability. Automating the analysis of echocardiographic images is therefore highly desirable, but also challenging because of the low image quality and the high amount of speckle noise.

Main Contributions

We have developed a novel optical-flow-based algorithm to estimate ventricular wall motion from B-mode echocardiograms. To account for typical heart motions such as contraction/expansion and shear, we use a local affine model for the velocity in space and time. An attractive feature of the affine motion model is that it gives also access to local strain-rate parameters that describe local myocardial deformation such as wall thickening. The motion parameters are estimated in the least-squares sense within a sliding spatio-temporal B-spline window. The estimation of large motions is made possible through the use of a coarse-to-fine multiscale strategy, which also adds robustness to the method.

An important aspect of the projet was to provide a visualization of the results that is meaningful to clinicians. The user can define a region of interest that is then tracked in time. Myocardial inward and outward motion is visualized by color coding the radial motion component with respect to the ventricular center. Two-dimensional strain-rate information is superimposed in the form of deforming ellipses. The display allows for an intuitive and simplified identification of regions with abnormal motion patterns.

The capabilities of the algorithm are demonstrated on a few illustrative in vitro and in vivo examples.

The project is carried out in close collaboration with cardiologists at the Medical Intensive Care Unit at the University Hospital Basel, Switzerland. This ensures that the algorithm meets real clinical needs and makes it possible to validate it in clinical practice.

Collaborations: Prof. Michael Unser and Muthuvel Arigovindan (BIG-EPFL); Dr. Patrick Hunziker and Dr. Christian Jansen (University Hospital of Basel)

Period: 2000-2005

Funding: Swiss National Science Foundation under Grant 3200-059517.99 and by the Swiss Heart Foundation

Major Publications

[1] 

M. Sühling, M. Arigovindan, P. Hunziker, M. Unser, "Multiresolution Moment Filters: Theory and Applications," IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 484-495, April 2004.

[2] 

M. Sühling, M. Arigovindan, C. Jansen, P. Hunziker, M. Unser, "Myocardial Motion Analysis from B-Mode Echocardiograms," IEEE Transactions on Image Processing, vol. 14, no. 4, pp. 525-536, April 2005.

[3] 

M. Sühling, C. Jansen, M. Arigovindan, P. Buser, S. Marsch, M. Unser, P. Hunziker, "Multiscale Motion Mapping—A Novel Computer Vision Technique for Quantitative, Objective Echocardiographic Motion Measurement Independent of Doppler: First Clinical Description and Validation," Circulation, vol. 110, no. 19, pp. 3093-3099, November 9, 2004.

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