Complex wavelet diffusion for enhancing ultrasound images of the laminar bone

The aim of this paper is to remove speckle noise and enhance the laminar bone structure in ultrasound images in order to aid the anesthesiologist during an epidural anesthesia needle insertion. In this regard, a direction and scale sensitive anisotropic diffusion (AD) algorithm called the complex wavelet diffusion algorithm is proposed. The proposed algorithm is tested on synthetic and real ultrasound images of the laminar bone and the results are compared with the speckle-reducing AD method. Results indicate that the proposed method can better highlight the diagonal-shaped laminar bones while removing speckle noise. Furthermore, the proposed despeckling algorithm is very fast providing the anesthesiologist with real-time information while an epidural injection is performed.

[1]  Scott T. Acton,et al.  Speckle reducing anisotropic diffusion , 2002, IEEE Trans. Image Process..

[2]  Purang Abolmaesumi,et al.  Speckle Noise Reduction of Medical Ultrasound Images in Complex Wavelet Domain Using Mixture Priors , 2008, IEEE Transactions on Biomedical Engineering.

[3]  T. Grau,et al.  Paramedian access to the epidural space: the optimum window for ultrasound imaging. , 2001, Journal of clinical anesthesia.

[4]  L. Parthiban,et al.  Speckle Noise Removal Using Contourlets , 2006, 2006 International Conference on Information and Automation.

[5]  Joao Sanches,et al.  Convex ultrasound image reconstruction with log-Euclidean priors , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  Robert N Rohling,et al.  Two-dimensional spatial compounding with warping. , 2004, Ultrasound in medicine & biology.

[7]  P. Shankar Speckle Reduction in Ultrasound B-Scans Using Weighted Averaging in Spatial Compounding , 1986, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[8]  Gerlind Plonka-Hoch,et al.  The Curvelet Transform , 2010, IEEE Signal Processing Magazine.

[9]  Robert Rohling,et al.  Automatic Detection of Lumbar Anatomy in Ultrasound Images of Human Subjects , 2010, IEEE Transactions on Biomedical Engineering.

[10]  Maryam Amirmazlaghani,et al.  A novel curvelet domain speckle suppression method for SAR images , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[11]  Carl-Fredrik Westin,et al.  Oriented Speckle Reducing Anisotropic Diffusion , 2007, IEEE Transactions on Image Processing.

[12]  M. S. Naceur,et al.  Despeckling of Intravascular Ultrasound images using curvelet transform , 2012, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT).

[13]  S. K. Jespersen,et al.  Multi-Angle Compound Imaging , 1998, Ultrasonic imaging.

[14]  M. Omair Ahmad,et al.  Wavelet-Based Despeckling of Medical Ultrasound Images with the Symmetric Normal Inverse Gaussian Prior , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[15]  M. Omair Ahmad,et al.  New Spatially Adaptive Wavelet-based Method for the Despeckling of Medical Ultrasound Images , 2007, 2007 IEEE International Symposium on Circuits and Systems.

[16]  N. Kingsbury Image processing with complex wavelets , 1999, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[17]  Richard Baraniuk,et al.  The Dual-tree Complex Wavelet Transform , 2007 .

[18]  Ying Li,et al.  Adaptive Enhancement with Speckle Reduction for SAR Images Using Mirror-Extended Curvelet and PSO , 2010, 2010 20th International Conference on Pattern Recognition.

[19]  Victor S. Frost,et al.  A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Jong-Sen Lee,et al.  Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  M. Omair Ahmad,et al.  Spatially adaptive thresholding in wavelet domain for despeckling of ultrasound images , 2009, IET Image Process..

[22]  Michael K. Ng,et al.  A New Total Variation Method for Multiplicative Noise Removal , 2009, SIAM J. Imaging Sci..

[24]  Kenneth E. Barner,et al.  Rayleigh-Maximum-Likelihood Filtering for Speckle Reduction of Ultrasound Images , 2007, IEEE Transactions on Medical Imaging.

[25]  Alin Achim,et al.  Novel Bayesian multiscale method for speckle removal in medical ultrasound images , 2001, IEEE Transactions on Medical Imaging.

[26]  Du-Ming Tsai,et al.  An improved anisotropic diffusion model for detail- and edge-preserving smoothing , 2010, Pattern Recognit. Lett..

[27]  José M. Bioucas-Dias,et al.  Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization , 2009, IEEE Transactions on Image Processing.

[28]  John W. Clark,et al.  Nonlinear multiscale wavelet diffusion for speckle suppression and edge enhancement in ultrasound images , 2006, IEEE Transactions on Medical Imaging.

[29]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  D. Kalaiyarasi DESPECKLING OF SAR IMAGES BY OPTIMIZING AVERAGED POWER SPECTRAL VALUE IN CURVELET DOMAIN , 2012 .

[31]  Joachim Weickert,et al.  Anisotropic diffusion in image processing , 1996 .

[32]  Robert Rohling,et al.  Adaptive ultrasound imaging of the lumbar spine for guidance of epidural anesthesia , 2009, Comput. Medical Imaging Graph..

[33]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Ke-ou Song,et al.  Speckle supression for medical ultrasound images based on modelling speckle with Rayleigh distribution in contourlet domain , 2008, 2008 International Conference on Wavelet Analysis and Pattern Recognition.

[35]  Jianguo Yu,et al.  Denoising Method for Echocardiographic Images Based on the Second Generation Curvelet Transform , 2009, 2009 2nd International Conference on Biomedical Engineering and Informatics.

[36]  Manish Khare,et al.  Despeckling of medical ultrasound images using Daubechies complex wavelet transform , 2010, Signal Process..

[37]  Ying Li,et al.  An Adaptive Method of Speckle Reduction and Feature Enhancement for SAR Images Based on Curvelet Transform and Particle Swarm Optimization , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[38]  Alexander A. Sawchuk,et al.  Adaptive restoration of images with speckle , 1987, IEEE Trans. Acoust. Speech Signal Process..

[39]  Vinod Kumar,et al.  Denoising of ultrasound images using Curvelet Transform , 2010, 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE).