squamous-cell
发表于 2025-3-21 17:45:23
书目名称Despeckling Methods for Medical Ultrasound Images影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0269145<br><br> <br><br>书目名称Despeckling Methods for Medical Ultrasound Images读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0269145<br><br> <br><br>
舰旗
发表于 2025-3-21 21:31:34
Wavelet and Fast Bilateral Filter Based Despeckling Method for Medical Ultrasound Images,se. Compared with other de-speckling methods, experiments show that the proposed method has improved de-speckling performance for medical ultrasound images. It not only has better reduction performance than other methods but also can preserve image details such as the edge of lesions.
合乎习俗
发表于 2025-3-22 03:15:46
Nonsubsampled Shearlet and Guided Filter Based Despeckling Method for Medical Ultrasound Images,ectiveness of the proposed method, experiments were conducted, and the results were compared to those of other existing denoising filters. These showed the proposed method performs more effectively at denoising and delivers clearer image detail.
初学者
发表于 2025-3-22 05:58:37
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小故事
发表于 2025-3-22 09:38:43
Carl C. Gaither,Alma E. Cavazos-Gaitherse. Compared with other de-speckling methods, experiments show that the proposed method has improved de-speckling performance for medical ultrasound images. It not only has better reduction performance than other methods but also can preserve image details such as the edge of lesions.
Stable-Angina
发表于 2025-3-22 14:41:57
Carl C. Gaither,Alma E. Cavazos-Gaitherectiveness of the proposed method, experiments were conducted, and the results were compared to those of other existing denoising filters. These showed the proposed method performs more effectively at denoising and delivers clearer image detail.
Stable-Angina
发表于 2025-3-22 18:43:35
Carl C. Gaither,Alma E. Cavazos-Gaitherg are discussed. Five categories of despeckle filters are presented. This chapter focuses on the comparison of despeckle filters for the breast ultrasound images. Despeckle filters which are classified into five categories (local adaptive filter, anisotropic diffusion filter, multi-scale filter, non
FLAG
发表于 2025-3-22 21:53:28
Carl C. Gaither,Alma E. Cavazos-Gaitheral properties of medical ultrasound image in the wavelet domain, an improved wavelet threshold function based on the universal wavelet threshold function is considered. The wavelet coefficients of noise-free signal and speckle noise are modeled as generalized Laplace distribution and Gaussian distri
不遵守
发表于 2025-3-23 02:31:58
Carl C. Gaither,Alma E. Cavazos-Gaitherion is applied to obtain a wavelet shrinkage algorithm. The coefficients of the low frequency sub-band in the wavelet domain are filtered by guided filter. The filtered image is then obtained by using the inverse wavelet transformation. Experiments with the comparison of the other seven de-speckling
辩论
发表于 2025-3-23 08:20:06
Carl C. Gaither,Alma E. Cavazos-Gaithermic additive model is developed to account for the medical ultrasound signal with speckle noise. Secondly, in accordance with the statistical property of the additive model, an adaptive wavelet shrinkage algorithm is applied to the noisy medical signal. Particularly, the algorithm is significant to