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A Review on Despeckling Filters in Ultrasound Images for Speckle Noise Reduction

机译:超声图像中的检测滤波器对散斑降噪的综述

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Ultrasound imaging is the most generally used in medical diagnosis and it is corrupted by speckle noise, which is multiplicative. For a better diagnosis, there is also a need to decrease the speckle noise in ultrasound images. Speckle noise minimization filters are identified to intensify the discernible endowment and retain critical features in ultrasound images to recuperate medical diagnosis. For the pronouncement of thyroid disorders, ultrasound imaging is mainly used. Considering the detection of medical images that are affected by speckle noise, multiple speckle-noise refine has been suggested. Speckle noise filters like filtering statistics, domain filtering transformation, filtering of Boolean logic, and filtering based on partial differential equations. This paper provides a systematic literature search on the latest approach for ultrasound image noise reduction.
机译:超声成像是医学诊断中最普遍用于的,并且它被斑点噪声损坏,即乘法。 为了更好的诊断,还需要降低超声图像中的斑点噪声。 识别出斑块噪声最小化过滤器以加强可辨别的禀赋,并在超声图像中保留关键特征,以恢复医疗诊断。 对于甲状腺疾病的发出,主要使用超声成像。 考虑到受散斑噪声影响的医学图像的检测,已经提出了多种斑点噪声。 散斑噪声过滤器如过滤统计,域过滤转换,过滤布尔逻辑,以及基于部分微分方程的过滤。 本文在最新方法中提供了系统的文献搜索,用于减少超声图像降噪。

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