A robust detail preserving anisotropic diffusion for speckle reduction in ultrasound images

<p>Abstract</p> <p>Background</p> <p>Speckles in ultrasound imaging affect image quality and can make the post-processing difficult. Speckle reduction technologies have been employed for removing speckles for some time. One of the effective speckle reduction technologies is anisotropic diffusion. Anisotropic diffusion technology can remove the speckles effectively while preserving the edges of the image and thus has drawn great attention from image processing scientists. However, the proposed methods in the past have different disadvantages, such as being sensitive to the number of iterations or low capability of preserving the details of the ultrasound images. Thus a detail preserved anisotropic diffusion speckle reduction with less sensitive to the number of iterations is needed. This paper aims to develop this kind of technologies.</p> <p>Results</p> <p>In this paper, we propose a robust detail preserving anisotropic diffusion filter (RDPAD) for speckle reduction. In order to get robust diffusion, the proposed method integrates Tukey error norm function into the detail preserving anisotropic diffusion filter (DPAD) developed recently. The proposed method could prohibit over-diffusion and thus is less sensitive to the number of iterations</p> <p>Conclusions</p> <p>The proposed anisotropic diffusion can preserve the important structure information of the original image while reducing speckles. It is also less sensitive to the number of iterations. Experimental results on real ultrasound images show the effectiveness of the proposed anisotropic diffusion filter.</p

A brief review on speckle noise reduction techniques for ultrasound images

Speckle noise, typically occurs in coherent imaging systems such as sonar, laser and ultrasound imaging, is an unwanted aftereffect of the image formation process in coherent imaging .Speckle reduction is an important issue for analysis of ultrasound images. In  ultrasound imaging system, the presence of speckle results decline  in image quality and makes it difficult for human interpretation and  diagnosis analysis.Numerous methods for speckle suppression were proposed. In this paper we have given the overview of  the speckle noise reduction modelalong with various filters which are commonly used for speckle reduction needed in ultrasound images. As speckle noise is dominated in ultrasound imaging, there is need of de-noising the ultrasound images before segmenting out the tumor regions. As border detection of these tumors should be highly accurate as final results of segmentation are dependent on it. Further we will explore the tumor edge detection and segmentation of infected liver ultrasound images