A robust index for global tissue deformation analysis in ultrasound images

Arnaud Brignol; Farida Cheriet; Catherine Laporte

doi:10.1117/12.2512589

15 March 2019 A robust index for global tissue deformation analysis in ultrasound images

Arnaud Brignol, Farida Cheriet, Catherine Laporte

Proceedings Volume 10949, Medical Imaging 2019: Image Processing; 109492X (2019) https://doi.org/10.1117/12.2512589
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

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.

Citation Download Citation

Arnaud Brignol, Farida Cheriet, and Catherine Laporte "A robust index for global tissue deformation analysis in ultrasound images", Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 109492X (15 March 2019); https://doi.org/10.1117/12.2512589

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