Abstract—Digital image acquisition and processing techniques plays important role in clinical diagnosis. Medical images are generally corrupted by noise during their acquisition and transmission. Removing noise from the original medical image is still a challenging problem for researchers. Ultrasound imaging is widely used for diagnosis over the other imaging modalities like Positron Emission Tomography (PET), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) due to its noninvasive nature, portable, accurate, harmless to the human beings and capability of forming real time imaging. The presence of signal dependant noise known as speckle degrades the usefulness of ultrasound imaging. The main purpose for speckle reduction is to improve the visualization of the image and it is the preprocessing step for segmentation, feature extraction and registration. Over a period, a number of methods have been proposed for speckle reduction in ultrasound imaging. While using techniques for speckle reduction as an aid for visualization, certain speckle contains diagnostic information and should be retained. The scope of this paper is to give an overview about despeckling techniques in ultrasound medical imaging.
Index Terms—speckle noise, speckle filters, wavelet transform, curvelet transform, contourlet transform
Cite: T. Joel and R. Sivakumar, "Despeckling of Ultrasound Medical Images: A Survey," Journal of Image and Graphics, Vol. 1, No. 3, pp. 161-165, September 2013. doi: 10.12720/joig.1.3.161-165
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