Fractional subpixel diffusion and fuzzy logic approach for ultrasound speckle reduction

  • Authors:

  • Yingtao Zhang;H. D. Cheng;Jiawei Tian;Jianhua Huang;Xianglong Tang

  • Affiliations:

  • School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China and Department of Computer Science, Utah State University, USA;Second Affiliated Hospital of Harbin Medical University, Harbin, China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

  • Venue:
  • Pattern Recognition
  • Year:
  • 2010

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Abstract

Speckle is the dominant source of noise in ultrasound imaging and is a kind of multiplicative noise. It is difficult to design a filter to remove speckle effectively. In this paper, a novel fuzzy subpixel fractional partial difference (FSFPD) for ultrasound speckle reduction is proposed. Euler-Lagrange equation acts as an increasing function of the fractional derivative's absolute value of the image intensity function. The fractional order partial difference is computed in the frequency and fuzzy domain with subpixel precision. We test the proposed method on both synthetic and real breast ultrasound (BUS) images. The comparisons of the experimental results show that the proposed method can preserve edges and structural details of ultrasound images well while removing speckle noise. In addition, the filtered images are assessed and evaluated by radiologists using double blind method. The results demonstrate that the discrimination rate of breast cancers has been highly improved after employing the proposed method.