Noise Equalization for Ultrafast Plane Wave Microvessel Imaging

Abstract

Ultrafast plane wave microvessel imaging significantly improves ultrasound Doppler sensitivity by increasing the number of Doppler ensembles that can be collected within a short period of time. The rich spatiotemporal plane wave data also enable more robust clutter filtering based on singular value decomposition. However, due to the lack of transmit focusing, plane wave microvessel imaging is very susceptible to noise. This paper was designed to: 1) study the relationship between ultrasound system noise (primarily time gain compensation induced) and microvessel blood flow signal and 2) propose an adaptive and computationally cost-effective noise equalization method that is independent of hardware or software imaging settings to improve microvessel image quality.

Figures

Figure 1

Power Doppler microvessel images filtered by a global SVD clutter filter (a), and a block-wise adaptive SVD clutter filter (b).

Figure 2

Different TGC settings of the Verasonics Vantage system that were used in this study.

Figure 3

Noise, tissue, and blood signal measurements under different TGC settings (upper panel in each column), together with corresponding power Doppler images (lower panel in each column). The two power Doppler images in each subpanel were acquired separately to obtain continuous blood signal measurements from 25 mm to 70 mm depth. (a)-(c) results before noise equalization. (d)-(f) results after noise equalization. All power Doppler images from (a) to (d) were displayed under the same dynamic range (color bars are in unit of dB). Dynamic range was fine tuned for the best visual appearance of the blood signal for the power Doppler images shown in (e) and (f). The yellow dashed line in (a) indicates extrapolation of the curve in order to show the depth where the signal amplitude should have been 6dB greater than noise.

Figure 4

(a) Noise field derived from the last rank singular value and singular vectors from SVD clutter filter. (b) 1-D noise profile obtained by averaging all pixels in (a) along lateral direction at each depth. (c) Smoothed 1-D noise profile. (d) Final equalization noise field obtained by replicating (c) along the lateral dimension. (e) Comparisons of derived noise profiles and measured noise profiles under different TGC settings.

Figure 5

Noise-equalized power Doppler maps using the derived noise field. All color bars are in unit of dB.

Figure 6

Power Doppler images before (left column) and after (right column) noise equalization obtained from various ultrasound systems, transducers, and imaging frequencies. All color bars are in unit of dB.

Figure 7

An example of directly using the 2D noise field derived from the last singular value and vector to perform noise equalization. (a) Original 2D noise map; (b) Heavily-smoothed noise map with a 2D median filter; (c) equalized power Doppler image using (b).