Comparative Study on Filter Methods of Medical Ultrasound Images

This paper presents a comparative study on six despeckling methods such as modified hybrid median filter, gabor filter, speckle reducing anisotropic diffusion, homomorphic filter, non-local mean filter and squeeze box filter. We select eight objective evaluation parameters, such as signal-to-ratio, contrast signal–to–noise ratio, figure of merit, least absolute error, peak signal-to-noise ratio, edge protection factor, quantitative parameters of despeckling, signal-to-minimum mean square error ratio, to quantify the performance of these filters. The comparative study will provide a good guidance for selecting a suitable filter in the ultrasound image processing.

[1]  Shin'ichi Koike Recursive Least Absolute Error Algorithm: Analysis and Simulations , 2002 .

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

[3]  Torbjørn Eltoft,et al.  Homomorphic wavelet-based statistical despeckling of SAR images , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Y Chen,et al.  Phase insensitive homomorphic image processing for speckle reduction. , 1996, Ultrasonic imaging.

[5]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[6]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[7]  Pierrick Coupé,et al.  Nonlocal Means-Based Speckle Filtering for Ultrasound Images , 2009, IEEE Transactions on Image Processing.

[8]  Göran Salomonsson,et al.  Image enhancement based on a nonlinear multiscale method , 1997, IEEE Trans. Image Process..

[9]  G. Umamaheswari,et al.  Modified hybrid median filter for effective speckle reduction in ultrasound images , 2010, ICN 2010.

[10]  D. Sakrison,et al.  On the Role of the Observer and a Distortion Measure in Image Transmission , 1977, IEEE Trans. Commun..

[11]  A. Tannenbaum,et al.  Despeckling of medical ultrasound images , 2006, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[12]  Scott T. Acton,et al.  Ultrasound Despeckling for Contrast Enhancement , 2010, IEEE Transactions on Image Processing.

[13]  Alin Achim,et al.  Wavelet-based ultrasound image denoising using an alpha-stable prior probability model , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).