Regions-of-interest based automated diagnosis of Parkinson’s disease using T1-weighted MRI
作者：
Highlights：
• First automated ROI based computer aided diagnosis of PD using T1-weighted MRI.
• Analysis of GM, WM and CSF from five ROIs individually, in pairs and triplets.
• Evaluation on acquired age and gender matched dataset (30 PD and 30 healthy).
• Forward feature selection based on mutual information outperforms ranking method.
• Best classification accuracy of 86.67% is achieved with SN for GM and SN + HP for WM.
摘要
•First automated ROI based computer aided diagnosis of PD using T1-weighted MRI.•Analysis of GM, WM and CSF from five ROIs individually, in pairs and triplets.•Evaluation on acquired age and gender matched dataset (30 PD and 30 healthy).•Forward feature selection based on mutual information outperforms ranking method.•Best classification accuracy of 86.67% is achieved with SN for GM and SN + HP for WM.
论文关键词：Parkinson’s disease,Feature extraction,Feature selection,Magnetic resonance imaging,Computer-aided diagnosis,Region-of-interest
论文评审过程：Available online 3 February 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.01.062
