多通道FLANN自适应滤波器用于彩色多普勒超声图像的斑点和脉冲噪声消除

2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3) Pub Date : 2020-02-01 DOI:10.1109/ICONC345789.2020.9117288

Manish Kumar, S. Jangir, S. Mishra, S. K. Choubey, D. K. Choubey

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引用次数: 1

摘要

彩色多普勒超声(CDUS)图像的混合噪声对图像特征的影响较大，传统的固定滤波器无法有效去除混合噪声。因此，在这种情况下，识别患者的内部阻塞或出血变得困难。为此，提出了一种进化多通道功能链路人工神经网络(M-FLANN)来去除CDUS图像中的斑点噪声。本文从定性和定量两方面对M-FLANN和其他五种竞争滤波器的性能进行了评价。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multi-Channel FLANN Adaptive Filter for Speckle & Impulse Noise Elimination from Color Doppler Ultrasound Images

The conventional fixed filters cannot be employed for removing the mixed noise of Color Doppler Ultrasound (CDUS) images because it affects the features of the image awkwardly. Consequently, identifying an internal blockage or hemorrhage of the patient become arduous in such conditions. Hence, the evolutionary multi-channel Functional Link Artificial Neural Network (M-FLANN) has been proposed to get rid of Speckle noise from the CDUS images. In this paper, the performance of the M-FLANN and other five competitive filters is evaluated in terms of qualitative and quantitative measures.

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2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3)

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