From Brain Imaging to Graph Analysis: a study on ADNI's patient cohort

14 May 2019  ·  Rui Zhang, Luca Giancardo, Danilo A. Pena, Yejin Kim, Hanghang Tong, Xiaoqian Jiang ·

In this paper, we studied the association between the change of structural brain volumes to the potential development of Alzheimer's disease (AD). Using a simple abstraction technique, we converted regional cortical and subcortical volume differences over two time points for each study subject into a graph. We then obtained substructures of interest using a graph decomposition algorithm in order to extract pivotal nodes via multi-view feature selection. Intensive experiments using robust classification frameworks were conducted to evaluate the performance of using the brain substructures obtained under different thresholds. The results indicated that compact substructures acquired by examining the differences between patient groups were sufficient to discriminate between AD and healthy controls with an area under the receiver operating curve of 0.72.

PDF Abstract

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here