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A robust index for global tissue deformation analysis in ultrasound images
Author(s): Arnaud Brignol; Farida Cheriet; Catherine Laporte
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Paper Abstract

In this paper, a new index for global 2D tissue deformation analysis without correlation is computed from an ultrasound video sequence. First, the vertical and horizontal projections of the frames are computed, followed by the mean of the outer product of the two projections. Finally, the deformation index is the relative variation of the mean of the outer product with respect to the first frame. The index was validated on simulated data (valve and echocardiography) and ex vivo (raw meat). In the latter case, an ultrasound probe was robotically moved along the vertical axis to compress the meat. Results showed that the proposed index is robust and highly correlated with the average relative displacement of the landmarks located on the boundaries of the deformed part for the simulations (r = 0.90) and with the probe motion in the ex vivo case (r = 0.83). In comparison, a simple normalized cross correlation approach gives poor results (r < 0.2) due to a lack of robustness in the tracking.

Paper Details

Date Published: 15 March 2019
PDF: 8 pages
Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 109492X (15 March 2019); doi: 10.1117/12.2512589
Show Author Affiliations
Arnaud Brignol, École de Technologie Supérieure (Canada)
Farida Cheriet, Ecole Polytechnique de Montréal (Canada)
Catherine Laporte, École de Technologie Supérieure (Canada)


Published in SPIE Proceedings Vol. 10949:
Medical Imaging 2019: Image Processing
Elsa D. Angelini; Bennett A. Landman, Editor(s)

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