Performance analysis of edge and detailed preserved speckle noise reduction filters for breast ultrasound images

Breast ultrasound is one of the powerful modalities for medical breast lesion imaging. Since ultrasound images are usually corrupted by speckle noise, it is important to perform effective despeckling process. Some filters perform despeckling process smoothly but they do not preserve the edges and details of ultrasound images. Edges and details are important features of lesion classifications. This paper aims at studying speckle noise reduction filters performance due to their ability for preserving edges and details of breast ultrasound images. Adaptive median filter, Frost´s filter, detailed preserved anisotropic diffusion filter and Wiener filter in wavelet domain are compared and evaluated on the basis of Peak Signal to Noise Ratio, Mean Squared Error, Average Difference, Mean, and Variance as second-order texture operator.