Quadratic Pulse Inversion Ultrasonic Imaging(QPI): A Two-Step Procedure for Optimization of Contrast Sensitivity and Specificity
We have previously introduced an ultrasonic imaging
approach that combines harmonic-sensitive pulse sequences with a
post-beamforming quadratic kernel derived from a second-order
Volterra filter (SOVF). This approach is designed to produce images
with high sensitivity to nonlinear oscillations from microbubble
ultrasound contrast agents (UCA) while maintaining high levels of
noise rejection. In this paper, a two-step algorithm for computing the
coefficients of the quadratic kernel leading to reduction of tissue
component introduced by motion, maximizing the noise rejection and
increases the specificity while optimizing the sensitivity to the UCA
is presented. In the first step, quadratic kernels from individual
singular modes of the PI data matrix are compared in terms of their
ability of maximize the contrast to tissue ratio (CTR). In the second
step, quadratic kernels resulting in the highest CTR values are
convolved. The imaging results indicate that a signal processing
approach to this clinical challenge is feasible.
[1] K. I. Kim and E. J. Powers, " A digital method of modeling
quadratically nonlinear systems with a general random input," IEEE
Trans. Acoust., Speech, Signal Processing, vol. 36, no. 11, pp. 1758-
1769, Nov. 1988.
[2] T. Koh and E. J. Powers, " Second-order volterra filtering and its
application to nonlinear system identification," IEEE Trans. Acoust.,
Speech, Signal Processing, vol. ASSP-33, no. 6, pp. 1445-1455, Dec.
1985.
[3] J. Ophir and K. J. Parker, " Contrast agent in diagnostic ultrasound,"
Ultrasound in Med. & Biol., vol. 15, no. 4, pp. 319-333, Nov. 1989.
[4] D. H. Simpson, C. T. Chin, and P. N. Burns, " Pulse inversion Doppler:
A new method for detecting nonlinear echoes from microbubble contrast
agent," IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 46, no. 2,
pp. 372-382, March 1999.
[5] H. Yao, P. Phukpattaranont, and E. S. Ebbini, " Post-beamforming
second-order Volterra filter for nonlinear pulse-echo imaging," in Proc.
ICASSP 2002, 2002, pp. 1133-1136.
[6] P. Phukpattaranont and E. S. Ebbini, "Post-beamforming second-order
Volterra filter for nonlinear pulse-echo ultrasonic imaging," IEEE Trans.
Ultrason., Ferroelect., Freg. Contr., vol. 50, no. 8, pp. 987-1001, Aug.
2003.
[7] P. Phukpattaranont, M. F. Al-Mistarihi and E. S. Ebbini, ÔÇÿPostbeamforming
Volterra filters for contrast-assisted ultrasonic imaging: Invivo
results," in Proc. IEEE Ultrason. Symp, 2003.
[8] M. F. Al-Mistarihi, E. S. Ebbini, "Quadratic Pulse Inversion Ultrasonic
Imaging (QPI): Detection of Low-Level Harmonic Activity of
Microbubble Contrast Agents," in Proc. ICASSP 2005, March 2005,
vol. 2, pp. 1009-1012.
[1] K. I. Kim and E. J. Powers, " A digital method of modeling
quadratically nonlinear systems with a general random input," IEEE
Trans. Acoust., Speech, Signal Processing, vol. 36, no. 11, pp. 1758-
1769, Nov. 1988.
[2] T. Koh and E. J. Powers, " Second-order volterra filtering and its
application to nonlinear system identification," IEEE Trans. Acoust.,
Speech, Signal Processing, vol. ASSP-33, no. 6, pp. 1445-1455, Dec.
1985.
[3] J. Ophir and K. J. Parker, " Contrast agent in diagnostic ultrasound,"
Ultrasound in Med. & Biol., vol. 15, no. 4, pp. 319-333, Nov. 1989.
[4] D. H. Simpson, C. T. Chin, and P. N. Burns, " Pulse inversion Doppler:
A new method for detecting nonlinear echoes from microbubble contrast
agent," IEEE Trans. Ultrason., Ferroelect., Freq. Contr., vol. 46, no. 2,
pp. 372-382, March 1999.
[5] H. Yao, P. Phukpattaranont, and E. S. Ebbini, " Post-beamforming
second-order Volterra filter for nonlinear pulse-echo imaging," in Proc.
ICASSP 2002, 2002, pp. 1133-1136.
[6] P. Phukpattaranont and E. S. Ebbini, "Post-beamforming second-order
Volterra filter for nonlinear pulse-echo ultrasonic imaging," IEEE Trans.
Ultrason., Ferroelect., Freg. Contr., vol. 50, no. 8, pp. 987-1001, Aug.
2003.
[7] P. Phukpattaranont, M. F. Al-Mistarihi and E. S. Ebbini, ÔÇÿPostbeamforming
Volterra filters for contrast-assisted ultrasonic imaging: Invivo
results," in Proc. IEEE Ultrason. Symp, 2003.
[8] M. F. Al-Mistarihi, E. S. Ebbini, "Quadratic Pulse Inversion Ultrasonic
Imaging (QPI): Detection of Low-Level Harmonic Activity of
Microbubble Contrast Agents," in Proc. ICASSP 2005, March 2005,
vol. 2, pp. 1009-1012.
@article{"International Journal of Electrical, Electronic and Communication Sciences:51714", author = "Mamoun F. Al-Mistarihi", title = "Quadratic Pulse Inversion Ultrasonic Imaging(QPI): A Two-Step Procedure for Optimization of Contrast Sensitivity and Specificity", abstract = "We have previously introduced an ultrasonic imaging
approach that combines harmonic-sensitive pulse sequences with a
post-beamforming quadratic kernel derived from a second-order
Volterra filter (SOVF). This approach is designed to produce images
with high sensitivity to nonlinear oscillations from microbubble
ultrasound contrast agents (UCA) while maintaining high levels of
noise rejection. In this paper, a two-step algorithm for computing the
coefficients of the quadratic kernel leading to reduction of tissue
component introduced by motion, maximizing the noise rejection and
increases the specificity while optimizing the sensitivity to the UCA
is presented. In the first step, quadratic kernels from individual
singular modes of the PI data matrix are compared in terms of their
ability of maximize the contrast to tissue ratio (CTR). In the second
step, quadratic kernels resulting in the highest CTR values are
convolved. The imaging results indicate that a signal processing
approach to this clinical challenge is feasible.", keywords = "Volterra Filter, Pulse Inversion, Ultrasonic Imaging,Contrast Agent.", volume = "4", number = "4", pages = "705-6", }