title: A robust detail preserving anisotropic diffusion for speckle reduction in ultrasound images.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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
  
  
  CONCLUSIONS
  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.
authors.affiliation: College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China.
authors.forename: Xiaoming
authors.initials: X
authors.lastname: Liu
authors.forename: Jun
authors.initials: J
authors.lastname: Liu
authors.forename: Xin
authors.initials: X
authors.lastname: Xu
authors.forename: Lei
authors.initials: L
authors.lastname: Chun
authors.forename: Jinshan
authors.initials: J
authors.lastname: Tang
authors.forename: Youping
authors.initials: Y
authors.lastname: Deng
mesh_terms: D000465:Algorithms; D000818:Animals; D016880:Anisotropy; D002417:Cattle; D007089:Image Enhancement; D021621:Imaging, Three-Dimensional; D014463:Ultrasonography