QB-Mode Ultrasonic Imaging

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DESCRIPTION (provided by applicant): A system for separating linear and nonlinear components of beamformed data from pulse-echo ultrasound imaging systems is proposed. This proposal investigates a system for separating linear and quadratic components of the echo data based on a second-order Volterra filter (SVF) model. The quadratic component of this decomposition can be presented in grayscale in a manner similar to the familiar B-mode imaging. This leads to a new form of grayscale imaging, referred to in this proposal as QB-mode imaging. QB-mode images are shown to be sensitive to quadratic signal components due to nonlinear propagation and/or microbubble ultrasound contrast agents (UCA). preliminary results clearly show that QB-mode images are superior to second harmonic (SH) images in both spatial and contrast resolution. Moreover, comparison with more specialized UCA imaging methods such as pulse inversion (PI) shows that QB-mode imaging is capable of achieving the same level of sensitivity and specificity to UCA without the need for multiple transmit pulses, thus preserving the frame rate of ultrasound imaging systems. This can be quite advantageous for imaging UCA for left ventricle opacification (LVO). In addition, QB-mode imaging has increased dynamic range allowing for display of tissue and contrast components on the same image allowing better diagnosis in radiologic examinations with or without UCA. This proposal requests funding to further investigate the characteristics of QB-mode imaging for a variety of imaging targets (e.g. high-frequency probes for breast cancer detection with or without UCA, phased array probes with UCA, etc.) In particular, we will investigate the optimization of the derivation of the SVF kernel coefficients for specific imaging scenarios, efficient adaptive implementation of the SVF, and pulsecompression properties of the quadratic component of the SVF in native QB-mode and in the presence of UCA. The real-time implementation of the optimal and adaptive SVFs using field programmable array (FPGA) technology will be emphasized throughout the project period.