Reducing Speckle Noise in Medical Ultrasound Image using Diffusion Filter Algorithm

Abstract

The quality of medical ultrasound is generally limited due to a number of factors, which originate from physical phenomena underlying the image acquisition. As a result, in the past few decades considerable efforts in the field of ultrasound imaging have been made for improving the image quality to make ultrasound imaging better for the perception of radiologists and more suitable for processing by autonomous machines for segmentation and registration. The major problem of ultrasound imaging technique is inheritance of Speckle noise. Speckle noise tends to reduce the image contrast and blur image details, thereby decreasing the quality and reliability of medical ultrasound. Many denoising methods such as Lee filter, Kuan filter and Frost filter have been developed so far for despeckling of ultrasound images but sometimes important diagnostic details are lost while denoising because of over smoothing. Diffusion filters are able to reduce noise but it requires large number of convergence .Wavelet based filters rarely cause over smoothing but they fail to perform well near edges. The proposed algorithm remove speckle noise without resulting into over smoothing and perform well near edges. Here In this thesis work, the proposed Algorithms designed to reduce speckle noise by the combination of PDE based Speckle Reducing Anisotropic Diffusion filter and wavelet based Threshold Shrink technique. Than The proposed algoritham is compared with spatial domain filters.