## 4 Discussion  
This paper presents an H-scan subtraction Doppler imaging technique based on ultrasound blood flow scattering identification to address several critical challenges of small-vessel Doppler imaging with ultrafast compounding plane waves. The flow phantom experiments with different blood concentrations, showing that the H-Scan is capable of estimating the relative size and spatial distribution of acoustic scattering objects. In the in vivo rabbit brain experiment, the H-Doppler method, together with global  
Figure 11: Comparison results of BWL-SVD filtering for conventional UCDI (left column) and H-Doppler (right column) under a 40-dB dynamic range; the block parameters used in this experiment are block size = height: 128, width: 24 and overlap = height: 120, width: 20. Zoomed images of the ROIs (white dashed rectangle and yellow dashed square) are given for each approach. The green dashed region was selected as the noise area for CNR calculation. The CNRs of the conventional UCDI with BWL-SVD filtering are 20.1 dB (white) and 19.7 dB (yellow). The CNRs of the H-Doppler approach we proposed upgrade to 23.2 dB (white) and 24.7 dB (yellow). The yellow and white arrows point at the identifiable blood vessels at the same depth in both UCDI and H-Doppler images. and block-wise local SVD (BWL-SVD) clutter filtering, is proposed to facilitate better power Doppler images with a significant improvement of background noise suppression. The detailed drawings also show the improvements of the H-Doppler method in contrast to CNR and its superiority to conventional UCDI techniques. To sum up, the advantage of H-Doppler in the detection of small blood flow benefits from the fact that B-channel data contributed by the convolution outputs of \(\mathrm{G}H_{\mathcal{B}}\) are more sensitive to Rayleigh scattering of the blood (the size is smaller than the wavelength of ultrasonic signals). As shown in Figure 9c,f, the SVD filtering results based on the B channel data essentially contain more blood flow information. Besides, the H-scan helped preserve the axial resolution, because the convolution filtering has a data smoothing effect [23]. Therefore, one of the simple approaches suggested in this paper is to perform power Doppler imaging immediately after the \(\mathrm{G}H_{\mathcal{B}}\) convolution filtering is applied to the original RF signal, which can improve the quality of the Doppler image to some extent. However, due to the involved tissue components and noise distribution in the biological tissue, it is difficult to determine the exact cutoff value of the high-order singular value thresholding in practice. The simple reason for that is the high-order SVT has always been based on the fair assumption that the blood flow signal and background noise have completely differing spatiotemporal characteristics. Moreover, the background noise is affected by many factors, such as ultrasonic attenuation and environmental vibration, which prevents us from obtaining a robust Doppler algorithm. In this study, we proposed a time domain subtraction method for H-scan power Doppler imaging, which can improve the CNR of the Doppler image. The proposed method only requires a preset low-order threshold in the process of SVD clutter filtering, which can be obtained directly through the estimation of blood flow Doppler frequency shift in practice. The feasibility of the previous time-domain subtraction method was proposed by [PERSON] [15]. They used a reference phantom to collect the background noise for the SVD filtering. Then, they used the noise field derived from the reference phantom to equalize the in vivo power Doppler image. The results show that the noise reduction method can increase the contrast of the Doppler image. However, the working sequence of this method is difficult to be applied in practice.