Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Xiangzhu Zeng"'
Autor:
Zhiyuan Ding, Yulang Huang, Xiangzhu Zeng, Shiyin Jiang, Shuyang Feng, Zhenduo Wang, Ling Wang, Zeng Wang, Yingying Xu, Yan Liu
Publikováno v:
NeuroImage, Vol 297, Iss , Pp 120755- (2024)
Resting-state functional magnetic resonance imaging (fMRI) provides an efficient way to analyze the functional connectivity between brain regions. A comprehensive understanding of brain functionality requires a unified description of multi-scale laye
Externí odkaz:
https://doaj.org/article/a9f9d86f0abb4bbb87575760aeb4ca7b
Autor:
Zhengrui Wang, Kailin Xia, Jiayi Li, Yanru Liu, Yumou Zhou, Linjing Zhang, Lu Tang, Xiangzhu Zeng, Dongsheng Fan, Qiong Yang
Publikováno v:
Biomedicines, Vol 12, Iss 4, p 810 (2024)
Stroke and dementia have been linked to the appearance of white matter hyperintensities (WMHs). Meanwhile, diffusion tensor imaging (DTI) might capture the microstructural change in white matter early. Specific dietary interventions may help to reduc
Externí odkaz:
https://doaj.org/article/40cee87adfbc4983ac08fc7522a416de
Autor:
Xinru Zhang, Chenghao Liu, Ni Ou, Xiangzhu Zeng, Zhizheng Zhuo, Yunyun Duan, Xiaoliang Xiong, Yizhou Yu, Zhiwen Liu, Yaou Liu, Chuyang Ye
Publikováno v:
NeuroImage, Vol 271, Iss , Pp 120041- (2023)
Brain lesion segmentation provides a valuable tool for clinical diagnosis and research, and convolutional neural networks (CNNs) have achieved unprecedented success in the segmentation task. Data augmentation is a widely used strategy to improve the
Externí odkaz:
https://doaj.org/article/e91006b75c194806875d6855cb24881c
Publikováno v:
NeuroImage: Clinical, Vol 38, Iss , Pp 103370- (2023)
Background and Objective: Both Alzheimer’s disease (AD) and Parkinson’s disease (PD) are progressive neurodegenerative diseases. Early identification is very important for the prevention and intervention of their progress. Hippocampus plays a cru
Externí odkaz:
https://doaj.org/article/63679622dc1046a6b23d7b672b62213f
Autor:
Qiong Yang, Xiangzhu Zeng, Zhou Yu, Xiaolu Liu, Lu Tang, Gaoqi Zhang, Danyang Tian, Nan Li, Dongsheng Fan
Publikováno v:
Frontiers in Neurology, Vol 13 (2022)
Background and PurposeConvexity subarachnoid hemorrhage (cSAH) may predict an increased recurrence risk in cerebral amyloid angiopathy (CAA)-related intracerebral hemorrhage (ICH) survivors. We aimed to investigate whether cSAH detected on CT was rel
Externí odkaz:
https://doaj.org/article/2efbbd5c318f45318023e43c003fa01f
Autor:
Feng Gao, Lu Tang, Dongsheng Fan, Nan Li, Xu Huang, Xiaolu Liu, Qiong Yang, Xiangzhu Zeng, Kailin Xia
Publikováno v:
Stroke and Vascular Neurology, Vol , Iss
Background and objective We investigated the association of APOE alleles with CT-based cerebral amyloid angiopathy (CAA) markers including subarachnoid extension (SAE) and finger-like projection (FLP).Methods We included patients with acute primary s
Externí odkaz:
https://doaj.org/article/f8de80abceb94e459839ba8ec231ba08
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Computer Methods and Programs in Biomedicine. 238:107597
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1b80af3017910a2c1f42ac8113ad96b
https://doi.org/10.1016/j.cmpb.2023.107597
https://doi.org/10.1016/j.cmpb.2023.107597
Publikováno v:
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
Hippocampus is an important anatomical region for Alzheimer's Disease (AD) identification. In this paper, a multi-scale attention-based convolutional network is proposed for AD identification. The two dimensional (2D) images in three different planes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edebcd881d4b2060288626ea795cde3d
https://doi.org/10.1109/embc48229.2022.9871944
https://doi.org/10.1109/embc48229.2022.9871944
Autor:
Ming Ni, Yuqing Zhao, Xiaoyi Wen, Ning Lang, Qizheng Wang, Wen Chen, Xiangzhu Zeng, Huishu Yuan
Publikováno v:
Quantitative imaging in medicine and surgery. 13(1)
The classification of calcaneofibular ligament (CFL) injuries on magnetic resonance imaging (MRI) is time-consuming and subject to substantial interreader variability. This study explores the feasibility of classifying CFL injuries using deep learnin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7946d88f7152bfa350087545e70443fb
https://pubmed.ncbi.nlm.nih.gov/36620152
https://pubmed.ncbi.nlm.nih.gov/36620152