Alzheimer’s disease classification based on graph kernel SVMs constructed with 3D texture features extracted from MR images
作者：
Highlights：
• Alzheimer’s disease classification based on graph kernel Support Vector Machines.
• Evaluation of image texture patterns of multiple brain regions in Alzheimer.
• Assessment of three distance metrics to measure node attributes differences.
• Threshold based method for graph edge removal to obtain discriminative graphs.
• Classification results comparable to other proposed graph-based models.
摘要
•Alzheimer’s disease classification based on graph kernel Support Vector Machines.•Evaluation of image texture patterns of multiple brain regions in Alzheimer.•Assessment of three distance metrics to measure node attributes differences.•Threshold based method for graph edge removal to obtain discriminative graphs.•Classification results comparable to other proposed graph-based models.
论文关键词：Graph-based classification,Texture extraction,Graph kernel,Alzheimer’s disease,Magnetic resonance image
论文评审过程：Received 28 December 2021, Revised 14 June 2022, Accepted 17 August 2022, Available online 24 August 2022, Version of Record 30 August 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118633
