New adaptive clutter rejection based on spectral analysis for ultrasound color Doppler imaging: phantom and in vivo abdominal study.
Effective rejection of time-varying clutter originating from slowly moving vessels and surrounding tissues is important for depicting hemodynamics in ultrasound color Doppler imaging (CDI). In this paper, a new adaptive clutter rejection method based on spectral analysis (ACR-SA) is presented for suppressing nonstationary clutter. In ACR-SA, tissue and flow characteristics are analyzed by singular value decomposition and tissue acceleration of backscattered Doppler signals to determine an appropriate clutter filter from a set of clutter filters. To evaluate the ACR-SA method, 20 frames of complex baseband data were acquired by a commercial ultrasound system equipped with a research package (Accuvix V10, Samsung Medison, Seoul, Korea) using a 3.5-MHz convex array probe by introducing tissue movements to the flow phantom (Gammex 1425 A LE, Gammex, Middleton, WI, USA). In addition, 20 frames of in vivo abdominal data from five volunteers were captured. From the phantom experiment, the ACR-SA method provided 2.43 dB (p <; 0.001) and 1.09 dB ( ) improvements in flow signal-to-clutter ratio (SCR) compared to static (STA) and down-mixing (ACR-DM) methods. Similarly, it showed smaller values in fractional residual clutter area (FRCA) compared to the STA and ACR-DM methods (i.e., 2.3% versus 5.4% and 3.7%, respectively, ). The consistent improvements in SCR from the proposed ACR-SA method were obtained with the in vivo abdominal data (i.e., 4.97 dB and 3.39 dB over STA and ACR-DM, respectively). The ACR-SA method showed less than 1% FRCA values for all in vivo abdominal data. These results indicate that the proposed ACR-SA method can improve image quality in CDI by providing enhanced rejection of nonstationary clutter.
Geunyong Park
Sunmi Yeo
Jae Jin Lee
Changhan Yoon
Hyun-Woo Koh
Hyungjoon Lim
Youngtae Kim
Hwan Shim
Yangmo Yoo
D000005:Abdomen / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000000981:diagnostic imaging; D009068:Movement / Q000502:physiology; D019047:Phantoms, Imaging; D018608:Ultrasonography, Doppler / Q000295:instrumentation / Q000379:methods*