Despeckling of medical ultrasound images by wavelet threshold optimisation Online publication date: Tue, 21-Oct-2014
by O. Saraniya; M. Ezhilarasi
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 15, No. 1, 2014
Abstract: Speckle noise is the primary factor that limits the contrast resolution of diagnostic ultrasound images, thereby limiting the detection of small low-contrast lesions and making the ultrasound images generally difficult for a non-specialist to interpret. Therefore, speckle is more often considered as a dominant source of noise in ultrasound imaging and should be filtered out by a robust despeckling technique. In this paper, we compare two despeckling techniques, based on wavelet thresholding. Bayes shrinkage and genetic-algorithm-based wavelet denoising despeckling technique are implemented. Wavelet functions were studied in detail and the two algorithms were implemented using the Haar wavelet as a wavelet function. The application of this new filter on ultrasound images has shown a superior performance over the state-of-the-art wavelet-based denoising methods in terms of visual quality and structural similarity index map.
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