Left ventricle motion estimation based on signal-dependent time-frequency representation

Marco Antonio Gutierrez; Heinar A. Weiderpass; Sergio Shiguemi Furuie

doi:10.1117/12.480397

2 May 2003 Left ventricle motion estimation based on signal-dependent time-frequency representation

Marco Antonio Gutierrez, Heinar A. Weiderpass, Sergio Shiguemi Furuie

Proceedings Volume 5031, Medical Imaging 2003: Physiology and Function: Methods, Systems, and Applications; (2003) https://doi.org/10.1117/12.480397
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

In current clinical practice, the noninvasive assessment of left ventricular deformation can be determined using all the principal imaging modalities, including contrast angiography, echocardiography, cine computed tomography, single photon emission tomography and magnetic resonance imaging. However, since the heart undergoes complex motion, proper characterization of its motion still remains an open and challenging research problem. A number of approaches for nonrigid motion analysis have been studied in the literature. Much of the effort has confined to estimate the displacement vector for each image point or optical flow. This is a challenging problem in image analysis because of a wide range of possible motions and the presence of noise in the image sets. In this work, we present an algorithm for computation of optical flow based on a signal-dependent radially Gaussian kernel that adapts over time. The adaptive kernel obtained from the proposed algorithm is used to estimate a 3D-frequency spectrum for a given pixel in a series of images. The orientation of the spectrum in the frequency domain is totally governed by the pixel velocity. In a recent contribution, a linear regression model is used over the spectrum to obtain the velocity components that are proportional to the pixel movement.

Citation Download Citation

Marco Antonio Gutierrez, Heinar A. Weiderpass, and Sergio Shiguemi Furuie "Left ventricle motion estimation based on signal-dependent time-frequency representation", Proc. SPIE 5031, Medical Imaging 2003: Physiology and Function: Methods, Systems, and Applications, (2 May 2003); https://doi.org/10.1117/12.480397

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