Speckle Reduction in Ultrasound Imaging
| AUTHOR | Zhang, Yan |
| PUBLISHER | LAP Lambert Academic Publishing (09/08/2010) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
Speckle noise is an inherent nature of ultrasound images. In this research a compounding method based on wavelet shrinkage denoising (WSD) is studied. Wavelet shrinkage denoising is adopted not only because the noise can be effectively removed in wavelet domain, but also because the decomposition- reconstruction process could successfully divide the radio-frequency (RF) signals into several subsignals, which can be envelope detected and then summed up to form the compounded image. Hence the denoising advantage of WSD is achieved along with speckle suppression of compounding method. In addition, because the contrast noise ratio (CNR) is a function of the weighting coefficients, optimal weighting is obtained via differentiating the CNR to further increase the image quality. To evaluate the developed compounding method, quantitative and qualitative performance of the developed method was carried out and compared with other existing methods for both the phantom data and in vivo data.
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Product Format
Product Details
ISBN-13:
9783838397597
ISBN-10:
3838397592
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
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Page Count:
84
Carton Quantity:
94
Product Dimensions:
6.00 x 0.20 x 9.00 inches
Weight:
0.30 pound(s)
Country of Origin:
US
Subject Information
BISAC Categories
Technology & Engineering | Engineering (General)
Descriptions, Reviews, Etc.
publisher marketing
Speckle noise is an inherent nature of ultrasound images. In this research a compounding method based on wavelet shrinkage denoising (WSD) is studied. Wavelet shrinkage denoising is adopted not only because the noise can be effectively removed in wavelet domain, but also because the decomposition- reconstruction process could successfully divide the radio-frequency (RF) signals into several subsignals, which can be envelope detected and then summed up to form the compounded image. Hence the denoising advantage of WSD is achieved along with speckle suppression of compounding method. In addition, because the contrast noise ratio (CNR) is a function of the weighting coefficients, optimal weighting is obtained via differentiating the CNR to further increase the image quality. To evaluate the developed compounding method, quantitative and qualitative performance of the developed method was carried out and compared with other existing methods for both the phantom data and in vivo data.
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Author:
Zhang, Yan
Yan Zhang is an associate professor in the School of Computing and Information Technology, University of Western Sydney. He received his PhD degree from the University of Sydney, Australia in 1994. Yan has research interests in knowledge update, program modification and evolution, logic programming, model checking, descriptive complexity theory, and information security. Yan has published many research papers in top international conferences and journals in his areas and obtained various national competitive research grants. Currently Yan is leading a research group Intelligent Systems Laboratory (ISL) at the University of Western Sydney.
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