科研之友
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摘要
Accurate image segmentation is an important task in medical image analysis as it can help us to better distinguish tumours from normal tissues. One of the important features of MRI images of glioma (a kind of brain tumour) is that the tumour shapes most often appear irregular and their contours indistinct. As such, node sets on the contour cannot be easily established and clustered together. In order to cluster node sets and so segment the glioma image, a novel model together with the method of Nash equilibrium is put forward. Firstly, a model of the Nash equilibrium with double allocation constraints is proposed. Secondly, the principle and formula of the Nash equilibrium based on entropy and standard deviation is proposed. Finally, the determination of the penalty parameter in SVM, using the novel Nash equilibrium to help cluster and segment the gliorna image is presented. Experiments demonstrate that the proposed model and method outperform the competing methods. It is shown that the proposed method can accurately and correctly segment glioma images.
