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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.
| Autorius: | Yan Zhang |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2010 |
| Knygos puslapių skaičius: | 84 |
| ISBN-10: | 3838397592 |
| ISBN-13: | 9783838397597 |
| Formatas: | 220 x 150 x 6 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Speckle Reduction in Ultrasound Imaging: Base on Wavelet Shrinkage Denoising Based Compounding Method“
