A New Dynamic Complex Baseband Pulse Compression Method for Chirp-Coded Excitation in Medical Ultrasound Imaging

Chirp-coded excitation can increase the signal-to-noise ratio (SNR) without degrading the axial resolution. Effective pulse compression (PC) is important to maintain the axial resolution and can be achieved with radio frequency (RF) and complex baseband (CBB) data (i.e., PC
_RF
and PC
_CBB
, respectively). PC
_CBB
can further reduce the computational complexity compared to PC
_RF
; however, PC
_CBB
suffers from a degraded SNR due to tissue attenuation. In this paper, we propose a new dynamic CBB PC method (PC
_CBB
-Dynamic) that can improve the SNR while compensating for tissue attenuation. The compression filter coefficients in the PC
_CBB
-Dynamic method are generated by dynamically changing the demodulation frequencies along with the depth. For PC, the obtained PC
_CBB
-Dynamic coefficients are independently applied to the in-phase and quadrature components of the CBB data. To evaluate the performance of the proposed method, simulation, phantom, and in vivo studies were conducted, and all three studies showed improved SNR, i.e., maximally 3.87, 7.41, and 5.75 dB, respectively. In addition, the measured peak range sidelobe level of the proposed method yielded lower values than the PC
_RF
and PC
_CBB
, and it also derived a suitable target location, i.e., a <;0.07-mm target location error, while maintaining the axial resolution. In an in vivo abdominal experiment, the PC
_CBB
-Dynamic method depicted brighter and clearer features in the hyperechoic region because highly correlated signals were produced by compensating for tissue attenuation. These results demonstrated that the proposed method can improve the SNR of chirp-coded excitation while preserving the axial resolution and the target location and reducing the computational complexity.