Functional Connectivity Analysis of Patients with Cerebral Infarction based Hierarchical Clustering Method

Qian Guo1, Hailing Wang1, Kai Wang1, Xin Pan2, Ling Zou1

  • 1Changzhou University and Changzhou Key Laboratory of Biomedical
  • 2Changzhou University

Details

11:30 - 13:30 | Fri 26 May | Emerald III, Rose, Narcissus & Jasmine | FrPS1T1.60

Session: Poster I

Abstract

In this paper, resting-state functional magnetic resonance imaging (R-fMRI) data of 15 patients with cerebral infarction were recorded first. Then, Pearson's correlation based hierarchical clustering (PCHC) method and independent component analysis (ICA) were performed to analyze and extract multiple correlation patterns. Finally, voxel-based aggregation index (VBAI) was used to quantitatively compare this two results and indicate that PCHC method has higher sensitivity than ICA.