@article { , title = {A novel model and method based on Nash equilibrium for medical image segmentation}, abstract = {Accurate image segmentation is a very 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 are most often appear irregular and their contours indistinct. As such, nodes on the contour cannot be easily established and clustered together. In order to cluster a 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 glioma image is presented. Experimental results demonstrate that the proposed model and method outperforms other competing methods. It is shown that the method can accurately and correctly segment glioma images.}, issn = {2156-7018}, issue = {5}, journal = {Journal of Medical Imaging and Health Informatics (JMIHI)}, note = {Comments and Suggestions : This is a terrible example of the publishing process - pay to publish (\$1080 on acceptance), then pay to access, and no archiving permitted at all. We do not have access to this article at all!!}, pages = {872-880}, publicationstatus = {Published}, publisher = {American Scientific Publishers}, url = {https://uwe-repository.worktribe.com/output/1435352}, volume = {8}, keyword = {Centre for Machine Vision, segmentation, cluster, Nash equilibrium, entropy, SVM}, year = {2018}, author = {Zhang, Tian and Zhang, Jing and Zhang, Jian and Smith, Melvyn and Hancock, Edwin} }