Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Peishan Dai"'
Autor:
Peishan Dai, Xiaoyan Zhou, Yilin Ou, Tong Xiong, Jinlong Zhang, Zailiang Chen, Beiji Zou, Xin Wei, Ying Wu, Manyi Xiao
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
The altered functional connectivity (FC) in amblyopia has been investigated by many studies, but the specific causality of brain connectivity needs to be explored further to understand the brain activity of amblyopia. We investigated whether the effe
Externí odkaz:
https://doaj.org/article/e0f5e9c9588a4a2f992590be55df3a37
Altered Spontaneous Brain Activity of Children with Unilateral Amblyopia: A Resting State fMRI Study
Publikováno v:
Neural Plasticity, Vol 2019 (2019)
Objective. This study is aimed at investigating differences in local brain activity and functional connectivity (FC) between children with unilateral amblyopia and healthy controls (HCs) by using resting state functional magnetic resonance imaging (r
Externí odkaz:
https://doaj.org/article/a7b80f14a19a4ed0970b649481b944b2
Publikováno v:
International Journal of Biomedical Imaging, Vol 2016 (2016)
Retinal fundus image plays an important role in the diagnosis of retinal related diseases. The detailed information of the retinal fundus image such as small vessels, microaneurysms, and exudates may be in low contrast, and retinal image enhancement
Externí odkaz:
https://doaj.org/article/e400e44496c84f80abf26d9b3239f87c
Autor:
Peishan Dai, Hanyuan Luo, Hanwei Sheng, Yali Zhao, Ling Li, Jing Wu, Yuqian Zhao, Kenji Suzuki
Publikováno v:
PLoS ONE, Vol 10, Iss 6, p e0127748 (2015)
Vessel segmentation in retinal fundus images is a preliminary step to clinical diagnosis for some systemic diseases and some eye diseases. The performances of existing methods for segmenting small vessels which are usually of more importance than the
Externí odkaz:
https://doaj.org/article/cb18a85cb33b45a5b52bf7984ce416a4
Publikováno v:
International Journal of Biomedical Imaging, Vol 2010 (2010)
Computer simulation of the biomechanical and biological heat transfer in ophthalmology greatly relies on having a reliable computer model of the human eye. This paper proposes a novel method on the construction of a geometric model of the human eye b
Externí odkaz:
https://doaj.org/article/ae224f95cc93479ca8f0328f4a004ed1
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. :1-10
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0768e8dd4e1c261e64d6461c1ffd71c
https://doi.org/10.1109/jbhi.2023.3278079
https://doi.org/10.1109/jbhi.2023.3278079
Publikováno v:
Neurocomputing. 507:157-165
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a65085a229f8e0a41477df7362e658cd
https://doi.org/10.1016/j.neucom.2022.08.004
https://doi.org/10.1016/j.neucom.2022.08.004
Publikováno v:
Physical and Engineering Sciences in Medicine. 45:867-882
Dynamic causal modeling (DCM) is a tool used for effective connectivity (EC) estimation in neuroimage analysis. But it is a model-driven analysis method, and the structure of the EC network needs to be determined in advance based on a large amount of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39bc028d49e6de3915ebf63e3bc34bcd
https://doi.org/10.1007/s13246-022-01156-w
https://doi.org/10.1007/s13246-022-01156-w
Autor:
Peishan Dai, Xiaoyan Zhou, Tong Xiong, Yilin Ou, Zailiang Chen, Beiji Zou, Weihui Li, Zhongchao Huang
Publikováno v:
Cerebellum (London, England).
Major depressive disorder (MDD) is a serious and widespread psychiatric disorder. Previous studies mainly focused on cerebrum functional connectivity, and the sample size was relatively small. However, functional connectivity is undirected. And, ther
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7a06fd6413b4628e1b3bcebdfa3a671
https://pubmed.ncbi.nlm.nih.gov/35933493
https://pubmed.ncbi.nlm.nih.gov/35933493
Autor:
Peishan Dai, Tong Xiong, Xiaoyan Zhou, Yilin Ou, Yang Li, Xiaoyan Kui, Zailiang Chen, Beiji Zou, Weihui Li, Zhongchao Huang, null The REST-meta-MDD Consortium
Publikováno v:
Behavioural brain research. 435
The current diagnosis of major depressive disorder (MDD) is mainly based on the patient's self-report and clinical symptoms. Machine learning methods are used to identify MDD using resting-state functional magnetic resonance imaging (rs-fMRI) data. H
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00f44e8ad50d382bff5a884a17398f8a
https://pubmed.ncbi.nlm.nih.gov/35995263
https://pubmed.ncbi.nlm.nih.gov/35995263