A novel coded excitation scheme to improve spatial and contrast resolution of quantitative ultrasound imaging.
Quantitative ultrasound (QUS) imaging techniques based on ultrasonic backscatter have been used successfully to diagnose and monitor disease. A method for improving the contrast and axial resolution of QUS parametric images by using the resolution enhancement compression (REC) technique is proposed. Resolution enhancement compression is a coded excitation and pulse compression technique that enhances the -6-dB bandwidth of an ultrasonic imaging system. The objective of this study was to combine REC with QUS (REC-QUS) and evaluate and compare improvements in scatterer diameter estimates obtained using the REC technique to conventional pulsing methods. Simulations and experimental measurements were conducted with a single-element transducer (f/4) having a center frequency of 10 MHz and a -6-dB bandwidth of 80%. Using REC, the -6-dB bandwidth was enhanced to 155%. Images for both simulation and experimental measurements contained a signal-to-noise ratio of 28 dB. In simulations, to monitor the improvements in contrast a software phantom with a cylindrical lesion was evaluated. In experimental measurements, tissue-mimicking phantoms that contained glass spheres with different scatterer diameters were evaluated. Estimates of average scatterer diameter in the simulations and experiments were obtained by comparing the normalized backscattered power spectra to theory over the -6-dB bandwidth for both conventional pulsing and REC. Improvements in REC-QUS over conventional QUS were quantified through estimate bias and standard deviation, contrast-to-noise ratio, and histogram analysis of QUS parametric images. Overall, a 51% increase in contrast and a 60% decrease in the standard deviation of average scatterer diameter estimates were obtained during simulations, while a reduction of 34% to 71% was obtained in the standard deviation of average scatterer diameter for the experimental results.
Sanchez
Jose R
JR
Dept. of Electr. & Comput. Eng., Bradley Univ., Peoria, IL, USA. jsm@bradley.edu
Pocci
Darren
D
Oelze
Michael L
ML
D000465:Algorithms; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted; D014463:Ultrasonography / Q000379:methods*