Dynamic thresholding networks for schizophrenia diagnosis

作者：

Highlights：

• Dynamic time warping method was used to describe the interactions among distributed brain regions.

• The dynamic attribute of FC network was taken into account.

• A novel time-varying window length DFC method was proposed.

• OMST algorithm was employed to eliminate the influence of spurious connections caused by noise in dynamic networks.

摘要

•Dynamic time warping method was used to describe the interactions among distributed brain regions.•The dynamic attribute of FC network was taken into account.•A novel time-varying window length DFC method was proposed.•OMST algorithm was employed to eliminate the influence of spurious connections caused by noise in dynamic networks.

论文关键词：Schizophrenia,rs-fMRI,Time-varying window length DFC,Dynamic time warping,Orthogonal minimum spanning tree

论文评审过程：Received 22 December 2018, Revised 13 March 2019, Accepted 17 March 2019, Available online 18 March 2019, Version of Record 22 March 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2019.03.007