Author_Institution :
Dept. of Electron. Eng., Sogang Univ., Seoul, South Korea
Abstract :
In ultrasound color Doppler imaging(CDI), effective clutter rejection is essential for estimating flow velocity and power. Since the clutter has time-varying characteristics, it is challenging to suppress it with a static clutter filter. In this paper, a new adaptive clutter rejection method based on spectral decomposition and tissue acceleration (ACR) for suppressing nonstationary clutter is presented. In the proposed method, tissue and flow characteristics are analyzed from singular value decomposition of backscattered Doppler signals to select optimal clutter filter from a bank of clutter filters. To evaluate the ACR method, phantom and in vivo experiments were conducted. For the phantom experiments, 20 frames of complex baseband data were acquired with a commercial ultrasound system (V10, Samsung Medison, Seoul, Korea) using a 3.5-MHz convex array probe by tapping over the flow phantom (Gammex 1425A LE, Gammex, Middleton, WI, USA) surface to mimic tissue movements. Similarly, 20 frames of in vivo liver data from a volunteer were also acquired. The performance of the proposed ACR method was compared with conventional clutter rejection methods, i.e., static (ST) and down-mixing (DM), using a commonly-used flow signal-to-clutter ratio (SCR) and fractional residual clutter area (FRCA). From the phantom experiments, the ACR method provided 2.03 dB and 0.98 dB improvements in SCR over the ST and DM methods. Similarly, ACR showed improvements in fractional residual clutter area (FRCA) compared to the ST and DM methods (i.e., 2.3% vs. 5.4 % and 3.7%, respectively). The consistent results were obtained with the in vivo experiments. The improvement in SCR from the ACR method is 4.90 dB and 3.98 dB, compared to the ST and DM methods. In addition, the ACR method showed less than 1% FRCA values for all 20 frames of in vivo data. These results indicate that the proposed ACR based on spectral decomposition and tissue acceleration can improve image quality in ultrasound color - oppler imaging by effectively removing the clutter.
Keywords :
Doppler measurement; adaptive filters; biological tissues; biomedical ultrasonics; clutter; data acquisition; flow visualisation; liver; medical image processing; phantoms; singular value decomposition; ultrasonic imaging; adaptive clutter rejection method; backscattered Doppler signals; bank clutter filters; commercial ultrasound system; complex baseband data acquisition; convex array probe; flow phantom; flow signal-to-clutter ratio; flow velocity estimation; fractional residual clutter area; frequency 3.5 MHz; image quality; in vivo liver data; optimal clutter filter; phantom experiments; power estimation; singular value decomposition; spectral decomposition; static clutter filter; time-varying characteristics; tissue acceleration; tissue movements; ultrasound color Doppler imaging; Clutter; Cutoff frequency; Doppler effect; Image color analysis; Imaging; In vivo; Ultrasonic imaging; Ultrasound color Doppler imaging; adaptive clutter rejection; nonstationary clutter; spectral analysis;