Ultrasound Image Denoising via Maximum a Posteriori Estimation of Wavelet Coefficients
PATRAS UNIV (GREECE)
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Speckle noise removal by means of digital image processors could improve the diagnostic potential of medical ultrasound. This paper addresses the speckle suppression issue wit bin the framework of wave let analysis. As a first step of our approach, the logarithm of the original image is decomposed into several scales through a multiresolution analysis employing the 2-D wavelet transform. Then, we design a maximum a posteriori MAP estimator, which relies on a recently introduced statistical representation for the wavelet coefficients of ultrasound images. We use an alpha-stable model to develop a blind noise-removal processor that performs a non-linear operation on the data. Finally we compare our technique to current state-of-the-art denoising methods applied on actual ultrasound images and we find it more effective both in terms of speckle reduction and signal detail preservation.
- Medicine and Medical Research
- Statistics and Probability