Coherent flow power Doppler imaging

Thumbnail Image




Journal Title

Journal ISSN

Volume Title

Repository Usage Stats



Ultrasonic flow detection is a widely used technique to detect vessel, measure blood flow velocities, and monitor perfusion. Conventional techniques include color Doppler imaging and power Doppler (PD) imaging. These methods depend on either the measurement of phase change or the detection of the power of backscattered echoes from blood. Both techniques are susceptible to noise. Common noise sources include thermal noise and clutter. The noise significantly deteriorates the performance of color Doppler imaging, because color Doppler imaging estimates the axial blood velocity from temporal changes in the echo phase, and phase change measurement is sensitive to noise. Power Doppler imaging measures the power of the temporal differences in backscattered echoes, and can provide higher sensitivity with small vessel and slow flow detection than color Doppler imaging at the expense of direction and velocity information. However, it requires a large ensemble length, limiting the frame rate to a few frames per second. The limitations of color Doppler imaging and power Doppler imaging are more severe in deep body vessel imaging due to depth dependent attenuation of the ultrasound waves. Therefore, for deep body vessel imaging, including liver vessel imaging and placental spiral artery imaging, better vessel detection techniques are desirable.

Coherent flow power Doppler (CFPD) imaging was proposed as a sensitive flow detection and imaging technique for slow flow and small vessels. In this work, we present the study on CFPD from principles to clinical evaluation.

The CFPD imaging technique detects blood flow from the spatial coherence of the blood signal. The short-lag spatial coherence (SLSC) beamformer is used for the measurement of spatial coherence. Because blood signals and common noise sources, including thermal noise reverberation clutter, have different spatial coherence properties, CFPD can suppress the noise.

The performance of CFPD in flow detection was evaluated with simulations and flow phantom experiments under various imaging conditions, and compared with the performance of PD. It is found that CFPD provides an improvement of Doppler signal-to-noise ratio (SNR) of 7.5-12.5 dB over PD in slow flow and small vessel imaging. The improvement in SNR translates to higher Doppler image contrast, faster frame rate, or lower limit-of-detection (LOD). In similar imaging conditions of slow flow, CFPD may detect up to 50% slower flow than PD.

The CFPD imaging technique was also implemented with novel pulse sequences, including plane-wave synthetic transmit aperture imaging, and diverging-wave synthetic transmit aperture imaging. For plane-wave synthetic transmit aperture imaging, the angular coherence theory was proposed to describe the coherence of backscattered waves corresponding to plane wave transmits at different steering angles. In addition, we also propose the coherent Kasai and Loupas estimators, which utilizes the coherence information of flow signals to provide velocity estimates with reduced uncertainty.

To demonstrate the clinical relevance of CFPD, we built a real-time CFPD imaging system and conducted a pilot clinical study with it. In the system, the CFPD technique was implemented on a Verasonics Vantage 256 research scanner. The software beamformer and CFPD processing were implemented on the graphics processing unit (GPU). The Doppler frame rate of the system is 10 frames per second for a field-of-view (FOV) of 10 cm axially and 4 cm laterally.

In the pilot clinical study, the liver vasculatures of 15 healthy human volunteers were imaged by a trained sonographer using the real-time CFPD system. The raw data corresponding to a 132 Doppler videos were captured and processed offline. The SNR of the vessels in the CFPD and PD images were measured and analyzed. In all of the 132 data sets, CFPD provides higher SNR than PD. The average improvement in SNR is 8.6 dB. From the visual analysis of the images, it can be seen that the improvement in SNR leads to more sensitive detection of small vessels in deeper parts of the liver.





Li, You (2017). Coherent flow power Doppler imaging. Dissertation, Duke University. Retrieved from


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.