A new neural network model for image segmentation

M. Liang, Qiu-Ming Ma, Dong-Guo Xu
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引用次数: 2

Abstract

In this paper, the problem of image segmentation using artificial neural network ( ANN) is discussed. A new ANN model for image segmentation is proposed which consists of two sub-networks in cascade, i.e. the master sub-network (MSN) and the auxiliary sub-network (ASN). The dynamics of this model is studied in details and the corresponding algorithm is described in the paper. Finally, the simulations are carried out for the medical image using the moment-preserving thresholding and the proposed ANN model, and the corresponding results indicate that the image segmented by the proposed ANN model is much better than that obtained by the moment-preserving thresholding.<>
一种新的图像分割神经网络模型
讨论了利用人工神经网络(ANN)进行图像分割的问题。提出了一种新的人工神经网络图像分割模型,该模型由主子网(MSN)和辅助子网(ASN)两个级联子网组成。本文对该模型的动力学进行了详细的研究,并给出了相应的算法。最后,对医学图像进行了保持矩阈值和人工神经网络模型的仿真,结果表明,人工神经网络模型的图像分割效果明显优于保持矩阈值模型。
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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