21 March 2014 Nonrigid motion compensation in B-mode and contrast enhanced ultrasound image sequences of the carotid artery
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Abstract
In this work, we investigate nonrigid motion compensation in simultaneously acquired (side-by-side) B-mode ultrasound (BMUS) and contrast enhanced ultrasound (CEUS) image sequences of the carotid artery. These images are acquired to study the presence of intraplaque neovascularization (IPN), which is a marker of plaque vulnerability. IPN quantification is visualized by performing the maximum intensity projection (MIP) on the CEUS image sequence over time. As carotid images contain considerable motion, accurate global nonrigid motion compensation (GNMC) is required prior to the MIP. Moreover, we demonstrate that an improved lumen and plaque differentiation can be obtained by averaging the motion compensated BMUS images over time. We propose to use a previously published 2D+t nonrigid registration method, which is based on minimization of pixel intensity variance over time, using a spatially and temporally smooth B-spline deformation model. The validation compares displacements of plaque points with manual trackings by 3 experts in 11 carotids. The average (± standard deviation) root mean square error (RMSE) was 99±74μm for longitudinal and 47±18μm for radial displacements. These results were comparable with the interobserver variability, and with results of a local rigid registration technique based on speckle tracking, which estimates motion in a single point, whereas our approach applies motion compensation to the entire image. In conclusion, we evaluated that the GNMC technique produces reliable results. Since this technique tracks global deformations, it can aid in the quantification of IPN and the delineation of lumen and plaque contours.
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Diego D. B. Carvalho, Zeynettin Akkus, Johan G. Bosch, Stijn C. H. van den Oord, Wiro J. Niessen, Stefan Klein, "Nonrigid motion compensation in B-mode and contrast enhanced ultrasound image sequences of the carotid artery", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90340N (21 March 2014); doi: 10.1117/12.2043549; https://doi.org/10.1117/12.2043549
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