Performance analysis of filtering techniques for speckle reduction on breast ultrasound images

Abstract

Breast cancer is one of the most frequent types of cancer occurs in women and also the leading cause of women's death in the world. Ultrasonography (USG) is the common modality which is used as the diagnosis tool due to its low cost and portability. It is used to early detect breast cancer. In the USG, the degradation of image edge character is indistinct or speckle noise frequently occurred at the time of the acquisition. It is important to carry out an effective process to reduce speckle noise. Some filters are proposed for reducing the speckle. However, the results cannot preserve the edges and the details of the USG images. This paper aims to study the performance of some filtering techniques in reducing speckle noise that can preserve the edges and the details of breast USG images. Multiple parameter measurements to determine image quality among others mean square error (MSE), signal to noise ratio (SNR), speckle index (C), average difference (AD) and contrast to speckle ratio (CSR) are used to compare and evaluate of Wiener filter, anisotropic diffusion filter (ADF), Perona-Malik filter, detail preserved anisotropic diffusion (DPAD) filter, speckle reduction anisotropic diffusion (SRAD), anisotropic diffusion filter with memory based on speckle statistics (ADMSS) and maximum homogeneity over a pixel neighborhood (m-homog). Based on the measurement parameter can specify filter that are providing a robust filter for de-speckling, preserving edges and details, while improving contrast of breast ultrasound images.