Tian Zhang
A novel model and method based on Nash equilibrium for medical image segmentation
Zhang, Tian; Zhang, Jing; Zhang, Jian; Smith, Melvyn; Hancock, Edwin
Authors
Jing Zhang
Jian Zhang
Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof
Edwin Hancock
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.
Citation
Zhang, T., Zhang, J., Zhang, J., Smith, M., & Hancock, E. (2018). A novel model and method based on Nash equilibrium for medical image segmentation. Journal of Medical Imaging and Health Informatics, 8(5), 872-880
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 11, 2017 |
Publication Date | Jun 1, 2018 |
Deposit Date | Mar 15, 2018 |
Journal | Journal of Medical Imaging and Health Informatics (JMIHI) |
Print ISSN | 2156-7018 |
Publisher | American Scientific Publishers |
Peer Reviewed | Peer Reviewed |
Volume | 8 |
Issue | 5 |
Pages | 872-880 |
Keywords | segmentation, cluster, Nash equilibrium, entropy, SVM |
Public URL | https://uwe-repository.worktribe.com/output/1435352 |
Publisher URL | http://www.aspbs.com/jmihi/contents_jmihi2018.htm#v8n5 |
You might also like
3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy
(2023)
Conference Proceeding
Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa
(2022)
Presentation / Conference
Towards machine vision for insect welfare monitoring and behavioural insights
(2022)
Journal Article