Frequency-space prediction filtering for acoustic clutter and random noise attenuation in ultrasound imaging

Frequency-space prediction filtering (FXPF), also known as FX deconvolution, is a technique originally developed for random noise attenuation in seismic imaging. FXPF attempts to reduce random noise in seismic data by modeling only real signals that appear as linear or quasilinear events in the aperture domain. In medical ultrasound imaging, channel radio frequency (RF) signals from the main lobe appear as horizontal events after receive delays are applied while acoustic clutter signals from off-axis scatterers and electronic noise do not. Therefore, FXPF is suitable for preserving only the main-lobe signals and attenuating the unwanted contributions from clutter and random noise in medical ultrasound imaging. We adapt FXPF to ultrasound imaging, and evaluate its performance using simulated data sets from a point target and an anechoic cyst. Our simulation results show that using only 5 iterations of FXPF achieves contrast-to-noise ratio (CNR) improvements of 67 % in a simulated noise-free anechoic cyst and 228 % in a simulated anechoic cyst contaminated with random noise of 15 dB signal-to-noise ratio (SNR). Our findings suggest that ultrasound imaging with FXPF attenuates contributions from both acoustic clutter and random noise and therefore, FXPF has great potential to improve ultrasound image contrast for better visualization of important anatomical structures and detection of diseased conditions.

[1]  Mok-Kun Jeong.  A Fourier transform-based sidelobe reduction method in ultrasound imaging , 2000 .

[2]  Juha T. Ylitalo.  On the signal-to-noise ratio of a synthetic aperture ultrasound imaging method , 1996 .

[3]  Dongwoon Hyun,et al.  Lesion Detectability in Diagnostic Ultrasound with Short-Lag Spatial Coherence Imaging , 2011, Ultrasonic imaging.

[4]  Junseob Shin,et al.  Breast ultrasound tomography with two parallel transducer arrays: preliminary clinical results , 2015, Medical Imaging.

[5]  P. E. Harris,et al.  Improving the performance of f-x prediction filtering at low signal-to-noise ratios , 1997 .

[6]  Pai-Chi Li,et al.  Adaptive imaging using the generalized coherence factor. , 2003, IEEE transactions on ultrasonics, ferroelectrics, and frequency control.

[7]  Junseob Shin,et al.  Aadaptive imaging with multi-phase apodization with cross-correlation: Phantom and in vivo results , 2015, 2015 IEEE International Ultrasonics Symposium (IUS).

[8]  J. Claerbout,et al.  Lateral prediction for noise attenuation by t-x and f-x techniques , 1995 .

[9]  J. Nasseri,et al.  Random and Coherent Noise Attenuation by Empirical Mode Decomposition , 2011 .

[10]  M. O'Donnell,et al.  Improved estimation of phase aberration profiles , 1997, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[11]  J. Camacho,et al.  Phase Coherence Imaging , 2009, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[12]  R. Cobbold.  Foundations of Biomedical Ultrasound , 2006 .

[13]  Junseob Shin,et al.  Synergistic enhancements of ultrasound image contrast with a combination of phase aberration correction and dual apodization with cross-correlation , 2012, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[14]  Öz Yilmaz,et al.  Seismic data processing , 1987 .

[15]  M. O'Donnell,et al.  Adaptive Aberration Correction of Abdominal Images Using PARCA , 1997, Ultrasonic imaging.

[16]  Junseob Shin,et al.  Improved image quality using phase aberration correction and Dual Apodization with Cross-correlation , 2011, 2011 IEEE International Ultrasonics Symposium.

[17]  Junseob Shin,et al.  Ultrasound transmission attenuation tomography using energy-scaled amplitude ratios , 2016, SPIE Medical Imaging.

[18]  Shaohuan Zu,et al.  Structure-oriented singular value decomposition for random noise attenuation of seismic data , 2015 .

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

[20]  Jørgen Arendt Jensen,et al.  Synthetic aperture ultrasound imaging. , 2006, Ultrasonics.

[21]  Kenneth M. Hanson,et al.  Breast ultrasound waveform tomography: using both transmission and reflection data, and numerical virtual point sources , 2014, Medical Imaging.

[22]  Junseob Shin,et al.  Breast ultrasound tomography with two parallel transducer arrays , 2016, SPIE Medical Imaging.

[23]  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.

[24]  Michael K. Chase.  Random noise reduction by FXY prediction filtering , 1992 .

[25]  Junseob Shin,et al.  Clutter suppression using Phase Apodization with Cross-correlation in ultrasound imaging , 2013, 2013 IEEE International Ultrasonics Symposium (IUS).

[26]  T. Misaridis,et al.  Use of modulated excitation signals in medical ultrasound. Part II: design and performance for medical imaging applications , 2005, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[27]  R. Kumaresan,et al.  Estimation of frequencies of multiple sinusoids: Making linear prediction perform like maximum likelihood , 1982, Proceedings of the IEEE.

[28]  J. Yen,et al.  Evaluating the robustness of dual apodization with cross-correlation , 2009, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[29]  Junseob Shin,et al.  Robust ultrasonic reverberation clutter suppression using Multi-Apodization with Cross-correlation , 2014, 2014 IEEE International Ultrasonics Symposium.

[30]  Brett Byram,et al.  Ultrasonic multipath and beamforming clutter reduction: a chirp model approach , 2014, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[31]  M. O'Donnell,et al.  Coherence factor of speckle from a multi-row probe , 1999, 1999 IEEE Ultrasonics Symposium. Proceedings. International Symposium (Cat. No.99CH37027).

[32]  Junseob Shin,et al.  Effects of dual apodization with cross- correlation on tissue harmonic and pulse inversion harmonic imaging in the presence of phase aberration , 2013, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[33]  Pai-Chi Li,et al.  Performance Evaluation of Coherence-Based Adaptive Imaging Using Clinical Breast Data , 2007, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[34]  L. Canales.  Random Noise Reduction , 1984 .

[35]  T. Christopher.  Finite amplitude distortion-based inhomogeneous pulse echo ultrasonic imaging , 1997, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[36]  Sven Treitel,et al.  The complex Wiener filter , 1974 .

[37]  Yangkang Chen,et al.  Random noise attenuation by f-x empirical mode decomposition predictive filtering , 2014 .

[38]  J.A. Jensen,et al.  Use of modulated excitation signals in medical ultrasound. Part I: basic concepts and expected benefits , 2005, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

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

[40]  G.R. Lockwood,et al.  Real-time 3-D ultrasound imaging using sparse synthetic aperture beamforming , 1998, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.