Adversarially Trained Persistent Homology Based Graph Convolutional Network for Disease Identification Using Brain Connectivity-Reference-Cited by-同舟云学术

Adversarially Trained Persistent Homology Based Graph Convolutional Network for Disease Identification Using Brain Connectivity

Published:2024-01 Issue:1 Volume:43 Page:503-516
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Bian Chenyuan¹^ORCID,Xia Nan²,Xie Anmu³,Cong Shan⁴,Dong Qian¹

Affiliation:

1. Shandong Provincial Key Laboratory of Digital Medicine and Computer-Assisted Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China

2. Institute of Digital Medicine and Computer-Assisted Surgery, Qingdao University, Qingdao, China

3. Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China

4. Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

http://xplorestaging.ieee.org/ielx7/42/10379496/10233896.pdf?arnumber=10233896

Reference51 articles.

1. Altered functional–structural coupling of large-scale brain networks in idiopathic generalized epilepsy

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4. Identifying Autism Spectrum Disorder From Resting-State fMRI Using Deep Belief Network

5. Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy

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