利用自编码器网络减少超声图像中的斑点噪声

Onur Karaoglu, H. Ş. Bilge, I. Uluer
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引用次数: 3

摘要

图像增强的目的是从噪声图像中获得清晰的图像,也用于超声图像。在实验研究中,与经典的图像增强方法不同,我们使用了深度学习方法。本文尝试利用深度学习方法之一的卷积去噪自编码器网络(convolutional去噪autoencoder network)去除臂丛神经系统超声图像中不同程度的斑点噪声。将实验研究结果与经典方法的结果进行了比较,发现所提出的方法比经典方法更成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reducing Speckle Noise from Ultrasound Images Using an Autoencoder Network
Image enhancement aims to obtain a clear image from a noisy image and it also uses for ultrasound images. In the experimental study, unlike classical image enhancement methods, deep learning method was used. Different levels of speckle noise added to the ultrasound images of the brachial plexus, which is known as the large nerve community under the armpit, were tried to be removed with the help of the convolutional denoising autoencoder network, which is one of the deep learning methods. The results obtained from the experimental study were compared with classical methods results and the proposed method was found to be more successful than classical methods.
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