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Appl. Sci. 2017, 7(1), 37;

Systematic Evaluation on Speckle Suppression Methods in Examination of Ultrasound Breast Images

School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China
College of Information Engineering, Shenzhen University, Shenzhen 518060, China
School of Electronics and Information, and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi’an 710072, China
Author to whom correspondence should be addressed.
Academic Editor: Kohji Masuda
Received: 18 September 2016 / Revised: 5 December 2016 / Accepted: 8 December 2016 / Published: 28 December 2016
(This article belongs to the Special Issue Biomedical Ultrasound)
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Breast ultrasound is an important tool used in the medical treatment and diagnosis of breast tumor. However, noise defined as speckles are generated inevitably. Although the existence of speckle may be beneficial to diagnosis if used by a well-trained observer, it often causes disturbance which negatively affects clinical diagnosis, not only by reducing resolution and contrast of ultrasound images, but also by adding difficulties to recognize tumor region accurately. In this paper, we investigate a number of popular de-speckling algorithms, including filters based on frequency domain, filters based on local statistical properties, filters based on minimum mean square error (MMSE), and filters based on Partial Differential Equation (PDE). Two visual measurement evaluation criteria, i.e., Mean to Variance Ratio (VMR) and Laplace Response of Domain (LRD), are chosen for the performance comparison of those filters in the application of ultrasound breast image filtering. Moreover, the filtering effect is further evaluated with respect to the segmentation accuracy of tumor regions. According to the evaluation results, we conclude that Bilateral Filter (BF) achieves the best visual effect. Although Weickert J Diffusion (WJD) and Total Variation (TV) can also obtain good visual effect and segmentation accuracy, they are very time-consuming. View Full-Text
Keywords: breast tumor; speckle suppression; comparison; ultrasound image breast tumor; speckle suppression; comparison; ultrasound image

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Feng, X.; Guo, X.; Huang, Q. Systematic Evaluation on Speckle Suppression Methods in Examination of Ultrasound Breast Images. Appl. Sci. 2017, 7, 37.

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