Hierarchical co-evolutionary clustering tree-based rough feature game equilibrium selection and its application in neonatal cerebral cortex MRI

作者：

Highlights：

• A novel hierarchical co-evolutionary clustering tree model (HCCT) is proposed.

• A mixed co-evolutionary game equilibrium scheme with adaptive dynamics is designed.

• The goal of global Nash equilibrium of HCCT model can be achieved.

• The proposed algorithm is applied in the segmentation of neonatal cerebral cortex.

摘要

•A novel hierarchical co-evolutionary clustering tree model (HCCT) is proposed.•A mixed co-evolutionary game equilibrium scheme with adaptive dynamics is designed.•The goal of global Nash equilibrium of HCCT model can be achieved.•The proposed algorithm is applied in the segmentation of neonatal cerebral cortex.

论文关键词：Hierarchical co-evolutionary cluster tree,Rough feature selection and classification,Mixed co-evolutionary game equilibrium,Neonatal cerebral cortex,Intensity non-uniformity levels

论文评审过程：Received 1 November 2017, Revised 29 January 2018, Accepted 30 January 2018, Available online 2 February 2018, Version of Record 27 February 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.01.053