Combining adaptive demodulation with singular value decomposition filtering for improved non-contrast perfusion ultrasound imaging

摘要

Tissue cluttercaused by patient and sonographerhand motion makes perfusion ultrasound imaging difficult. We previously introduced an adaptive frequency and amplitude demodulation scheme to address this challenge. Our initial implementation used a conventional high-pass infinite impulse response (ⅡR) filter to attenuate the tissue signal after applying adaptivedemodulation. However, othergroups have shown that singular value decomposition (SVD) filtering is superior to conventional frequency domain filters. Here we evaluate the SVD filter both in comparison and in conjunction with our proposed adaptive demodulation technique. Blood-to-background SNRs were compared using power Doppler images made from single small vessel simulations with realistic tissue clutter. Additionally, filtering methods were qualitatively assessed using power Doppler images of a cut-in-half perfusion-mimicking phantom. Furthermore, in vivo power Doppler images were compared before and after muscle contraction. SVD filtering with adaptive demodulation resulted in a 7dB increase in simulated blood-to-background SNR compared to a conventional ⅡR filter and a 54.6% increase in power after in vivo muscle contraction compared to a 1.74% increase using a conventional ⅡR filter.