Speckle noise reduction for ultrasound images by using speckle reducing anisotropic diffusion and Bayes threshold
- Authors
- Choi, Hyunho; Jeong, Je chang
- Issue Date
- 2019
- Publisher
- IOS PRESS
- Keywords
- Ultrasound imaging; speckle noise; discrete wavelet transform; srad; bayes threshold
- Citation
- JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY, v.27, no.5, pp.885 - 898
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY
- Volume
- 27
- Number
- 5
- Start Page
- 885
- End Page
- 898
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2971
- DOI
- 10.3233/XST-190515
- ISSN
- 0895-3996
- Abstract
- Ultrasound imaging has been used for diagnosing lesions in the human body. In the process of acquiring ultrasound images, speckle noise may occur, affecting image quality and auto-lesion classification. Despite the efforts to resolve this, conventional algorithms exhibit poor speckle noise removal and edge preservation performance. Accordingly, in this study, a novel algorithm is proposed based on speckle reducing anisotropic diffusion (SRAD) and a Bayes threshold in the wavelet domain. In this algorithm, SRAD is employed as a preprocessing filter, and the Bayes threshold is used to remove the residual noise in the resulting image. Compared to the conventional filtering techniques, experimental results showed that the proposed algorithm exhibited superior performance in terms of peak signal-to-noise ratio (average = 28.61 dB) and structural similarity (average = 0.778).
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