A novel PBL-McRBFN-RFE approach for identification of critical brain regions responsible for Parkinson’s disease

作者：

Highlights：

• Early detection of Parkinson’s disease using MRI and PBL-McRBFN classifier.

• Whole brain morphometry to detect significant volumetric change in gray matter.

• Recursive feature elimination to detect critical brain region responsible for PD.

• Identified brain regions are detected as affected region in medical autopsy.

摘要

•Early detection of Parkinson’s disease using MRI and PBL-McRBFN classifier.•Whole brain morphometry to detect significant volumetric change in gray matter.•Recursive feature elimination to detect critical brain region responsible for PD.•Identified brain regions are detected as affected region in medical autopsy.

论文关键词：Parkinson’s disease,Magnetic resonance imaging,Voxel-based morphometry,Meta-cognitive learning algorithm,Radial basis function network classifier,Recursive feature selection

论文评审过程：Available online 31 July 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.07.073