Segmentation of ultrasound images by using quantizer neural network

Z. Dokur, M. N. Kurnaz, T. Ölmez
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引用次数: 6

Abstract

A quantizer neural network (QNN) is proposed for the segmentation of ultrasound images. The elements of the feature vectors are formed by the image intensities within the neighborhood of the pixel of interest. The QNN is a hybrid neural network structure, which is trained by genetic algorithms. The genetic algorithms are used to find optimum values for the weights of the nodes. The hybrid neural network is compared with a multilayer perceptron (MLP) for the segmentation of ultrasound images.
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基于量化神经网络的超声图像分割
提出了一种量化神经网络(QNN)用于超声图像的分割。特征向量的元素由感兴趣像素附近的图像强度形成。QNN是一种混合神经网络结构,采用遗传算法进行训练。采用遗传算法寻找节点权值的最优值。将混合神经网络与多层感知器(MLP)进行超声图像分割的比较。
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