A large margin algorithm for automated segmentation of white matter hyperintensity

作者：

Highlights：

• A novel large margin method for white matter hyperintensity segmentation is proposed.

• A supervised large margin algorithm is proposed to learn a global classifier.

• A semi-supervised large margin classifier is learned for refinement on test subject.

• The proposed model shows competitive performance on subjects with vascular disease.

摘要

•A novel large margin method for white matter hyperintensity segmentation is proposed.•A supervised large margin algorithm is proposed to learn a global classifier.•A semi-supervised large margin classifier is learned for refinement on test subject.•The proposed model shows competitive performance on subjects with vascular disease.

论文关键词：Supervised learning,Semi-supervised learning,Segmentation,White matter hyperintensity,Brain MRI

论文评审过程：Received 10 July 2017, Revised 6 December 2017, Accepted 17 December 2017, Available online 18 December 2017, Version of Record 30 December 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.12.016