A motion-based approach to abdominal clutter reduction

In ultrasound images, clutter is a noise artifact most easily observed in anechoic or hypoechoic regions. It appears as diffuse echoes overlying anatomical structures of diagnostic importance, obscuring tissue borders and reducing image contrast. A novel clutter reduction method for abdominal images is proposed, wherein the abdominal wall is displaced during successive-frame image acquisitions. A region of clutter distal to the abdominal wall was observed to move with the abdominal wall, and finite impulse response (FIR) and blind source separation (BSS) motion filters were implemented to reduce this clutter. The proposed clutter reduction method was tested in simulated and phantom data and applied to fundamental and harmonic in vivo bladder and liver images from 2 volunteers. Results show clutter reductions ranging from 0 to 18 dB in FIR-filtered images and 9 to 27 dB in BSS-filtered images. The contrast-to-noise ratio was improved by 21 to 68% and 44 to 108% in FIR- and BSS-filtered images, respectively. Improvements in contrast ranged from 4 to 12 dB. The method shows promise for reducing clutter in other abdominal images.

[1]  Francesco Viola,et al.  Time-Domain Optimized Near-Field Estimator for Ultrasound Imaging: Initial Development and Results , 2008, IEEE Transactions on Medical Imaging.

[2]  P L Carson,et al.  A modeled study for diagnosis of small anechoic masses with ultrasound. , 1977, Radiology.

[3]  Francois Vignon,et al.  Capon beamforming in medical ultrasound imaging with focused beams , 2008, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[4]  M. Averkiou,et al.  Tissue harmonic imaging , 2000, 2000 IEEE Ultrasonics Symposium. Proceedings. An International Symposium (Cat. No.00CH37121).

[5]  Gregg E Trahey,et al.  Adaptive Clutter Filtering via Blind Source Separation for Two-Dimensional Ultrasonic Blood Velocity Measurement , 2002, Ultrasonic imaging.

[6]  K. Boone,et al.  Effect of skin impedance on image quality and variability in electrical impedance tomography: a model study , 1996, Medical and Biological Engineering and Computing.

[7]  Carlo Bartolozzi,et al.  Tissue harmonic and contrast-specific imaging: back to gray scale in ultrasound , 2002, European Radiology.

[8]  M O'Donnell,et al.  Improved detectability with blocked element compensation. , 1994, Ultrasonic imaging.

[9]  J. Jensen,et al.  Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers , 1992, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[10]  S. Yarmenitis,et al.  Ultrasound of the gallbladder and the biliary tree , 2002, European Radiology.

[11]  M. O'Donnell,et al.  Synthetic aperture imaging for small scale systems , 1995, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[12]  P. Burns,et al.  Pulse inversion Doppler: a new method for detecting nonlinear echoes from microbubble contrast agents , 1997, 1997 IEEE Ultrasonics Symposium Proceedings. An International Symposium (Cat. No.97CH36118).

[13]  Gregg E. Trahey,et al.  Quantitative Assessment of the Magnitude, Impact and Spatial Extent of Ultrasonic Clutter , 2008, Ultrasonic imaging.

[14]  Gregg E. Trahey,et al.  Simulation and experimental analysis of ultrasonic clutter in fundamental and harmonic imaging , 2009, Medical Imaging.

[15]  G. Trahey,et al.  Magnitude, origins, and reduction of abdominal ultrasonic clutter , 2008, 2008 IEEE Ultrasonics Symposium.

[16]  J. Arendt.  Paper presented at the 10th Nordic-Baltic Conference on Biomedical Imaging: Field: A Program for Simulating Ultrasound Systems , 1996 .

[17]  J D Thomas,et al.  Tissue harmonic imaging: why does it work? , 1998, Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography.

[18]  W.F. Walker,et al.  A constrained adaptive beamformer for medical ultrasound: initial results , 2002, 2002 IEEE Ultrasonics Symposium, 2002. Proceedings..

[19]  L Pourcelot,et al.  Clinical use of ultrasound tissue harmonic imaging. , 1999, Ultrasound in medicine & biology.

[20]  James R. Fienup,et al.  Nonlinear apodization for sidelobe control in SAR imagery , 1995 .

[21]  Jørgen Arendt Jensen,et al.  Stationary echo canceling in velocity estimation by time-domain cross-correlation , 1993, IEEE Trans. Medical Imaging.

[22]  Mia Hubert,et al.  ROBPCA: A New Approach to Robust Principal Component Analysis , 2005, Technometrics.

[23]  Mia Hubert,et al.  LIBRA: a MATLAB library for robust analysis , 2005 .

[24]  X. Gong,et al.  Improvement of tissue harmonic imaging using the pulse-inversion technique. , 2005, Ultrasound in medicine & biology.

[25]  G.E. Trahey,et al.  Rapid tracking of small displacements with ultrasound , 2006, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[26]  P. Burns,et al.  Tissue harmonic imaging: is it a benefit for bile duct sonography? , 2001, AJR. American journal of roentgenology.

[27]  Jesse Yen,et al.  Sidelobe suppression in ultrasound imaging using dual apodization with cross-correlation , 2008, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[28]  Gregg E Trahey,et al.  BSS-based filtering of physiological and ARFI-induced tissue and blood motion. , 2003, Ultrasound in medicine & biology.

[29]  F. Duck.  Nonlinear acoustics in diagnostic ultrasound. , 2002, Ultrasound in medicine & biology.