A recursive filter for temporal analysis of cardiac motion

A framework for temporal analysis of left ventricular (LV) endocardial wall motion is presented. This approach uses a novel technique of two-dimensional harmonic estimation to model the periodic nature of cardiac motion. A method for flow vector computation is presented which defines a relationship between image-derived, shape-based correspondences and a more desirable, smoothly varying, set of correspondences. A sequential filter is then constructed which takes into consideration this relationship as well as knowledge of temporal trends. Experimental results for contours derived from cycles of actual cardiac magnetic resonance images are presented. Applications to the analysis of regional LV wall function are discussed.<<ETX>>

[1]  Jake K. Aggarwal,et al.  Computer Analysis of Moving Polygonal Images , 1975, IEEE Transactions on Computers.

[2]  S. Glantz,et al.  Quantitative Left Ventricular Wall Motion Analysis: A Comparison of Area, Chord Radial Methods , 1979, Circulation.

[3]  S.M. Kay,et al.  Spectrum analysis—A modern perspective , 1981, Proceedings of the IEEE.

[4]  Arye Nehorai,et al.  Adaptive comb filtering for harmonic signal enhancement , 1986, IEEE Trans. Acoust. Speech Signal Process..

[5]  G T Meester,et al.  Quantitative assessment of regional left ventricular motion using endocardial landmarks. , 1986, Journal of the American College of Cardiology.

[6]  G F Oster,et al.  The Physics of Cell Motility , 1987, Journal of Cell Science.

[7]  Petre Stoica,et al.  Decentralized Control , 2018, The Control Systems Handbook.

[8]  Guido Valli,et al.  A visual framework for the study of cardiac motion , 1990, [1990] Proceedings Computers in Cardiology.

[9]  R. Leahy,et al.  Computation of 3-D velocity fields from 3-D cine CT images of a human heart. , 1991, IEEE transactions on medical imaging.

[10]  A. Pentland,et al.  Non-rigid motion and structure from contour , 1991, Proceedings of the IEEE Workshop on Visual Motion.

[11]  James S. Duncan,et al.  Measurement of non-rigid motion using contour shape descriptors , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  James S. Duncan,et al.  Boundary Finding with Parametrically Deformable Models , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Nicholas Ayache,et al.  Tracking Points on Deformable Objects Using Curvature Information , 1992, ECCV.

[14]  John S. Duncan,et al.  A constrained analytic solution for tracking non-rigid motion of the left ventricle , 1992, [1992] Proceedings of the Eighteenth IEEE Annual Northeast Bioengineering Conference.

[15]  Nicholas Ayache,et al.  Non-Rigid Motion Analysis in Medical Images: a Physically Based Approach , 1993, IPMI.

[16]  Richard Szeliski,et al.  Tracking with Kalman snakes , 1993 .

[17]  Frederic Fol Leymarie,et al.  Tracking Deformable Objects in the Plane Using an Active Contour Model , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  James S. Duncan,et al.  Shape-based tracking of naturally occurring annuli in image sequences , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.