Tetrahedral spectral feature-Based bayesian manifold learning for grey matter morphometry: Findings from the Alzheimer's disease neuroimaging initiative.

导出 OA

翻译打印收藏纠错

作者： Yonghui,Fan ^[1] ; Gang,Wang ^[2] ; Qunxi,Dong ^[1] ; Yuxiang,Liu ^[1] ; Natasha,Leporé ^[3] ; Yalin,Wang ^[4]

作者单位： School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA. ^[1] School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA; School of Information and Electrical Engineering, Ludong University, Yantai, China. ^[2] CIBORG Lab, Department of Radiology Children's Hospital Los Angeles, Los Angeles, CA, USA. ^[3] School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA. Electronic address: ylwang@asu.edu. ^[4]

关键词 Alzheimer’S disease Bayesian manifold learning Magnetic resonance imaging (MRI)Spectral shape analysis Tetrahedral mesh

主题词阿尔茨海默病(Alzheimer Disease);贝叶斯定理(Bayes Theorem);脑(Brain);人类(Humans);磁共振成像(Magnetic Resonance Imaging)

DOI 10.1016/j.media.2021.102123

PMID 34214958

发布时间 2024-04-02

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交