Nonrigid motion estimation of ultrasound image sequences using an adaptive deformable mesh

Fai Yeung; Stephen F. Levinson; Kevin J. Parker

doi:10.1117/12.310961

24 June 1998 Nonrigid motion estimation of ultrasound image sequences using an adaptive deformable mesh

Fai Yeung, Stephen F. Levinson, Kevin J. Parker

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310961
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

By exploiting the correlation of ultrasound speckle patterns that result from scattering by underlying tissue elements, 2D tissue motion can be theoretically recovered by tracking the apparent movement of the speckle patterns. Speckle tracking, however, is an ill-posed inverse problem because of temporal decorrelation of the speckle patterns and the inherent low signal-to-noise ratio of medical ultrasonic images. This paper investigates the use of an adaptive deformable mesh for non-rigid tissue motion recovery from ultrasound images. The nodes connecting the mesh elements are allocated adaptively to stable speckle patterns that are less susceptible to temporal decorrelation. We use the approach of finite element analysis in manipulating the irregular mesh elements. A novel deformable block matching algorithm, making use of a Lagrange element for higher-order description of local motions, is proposed to estimate a non- rigid motion vector at each node. In order to ensure that the motion estimates are admissible to a physically plausible solution, the nodal displacements are regularized by minimizing the strain energy of the mesh deformations. Experiments based on ultrasound images of muscle contraction and on computer simulations have shown that the proposed algorithm can successfully track non-rigid displacement fields.

Citation Download Citation

Fai Yeung, Stephen F. Levinson, and Kevin J. Parker "Nonrigid motion estimation of ultrasound image sequences using an adaptive deformable mesh", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310961

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