DETECTING STRUCTURAL BRAIN CONNECTIVITY DIFFERENCES IN DEMENTIA THROUGH A CONDUCTANCE MODEL

被引：0

作者：

Frau-Pascual, Aina ^{[1
]}

Augustinack, Jean ^{[1
]}

Varadarajan, Divya ^{[1
]}

Yendiki, Anastasia ^{[1
]}

Fischl, Bruce ^{[1
,2
]}

Aganj, Iman ^{[1
,2
]}

机构：

[1] Harvard Med Sch, Massachusetts Gen Hosp, AA Martinos Ctr Biomed Imaging, Boston, MA 02115 USA

[2] MIT, Comp Sci & Artificial Intelligence Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA

来源：

CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS | 2019年

基金：

美国国家卫生研究院;

关键词：

connectivity; conductance; diffusion MRI; Alzheimer's disease; dementia; ALZHEIMERS-DISEASE; MRI;

D O I：

10.1109/ieeeconf44664.2019.9048747

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Structural brain connectivity has been shown to be sensitive to the changes that the brain undergoes during Alzheimer's disease (AD) progression. In this work, we use our recently proposed structural connectivity quantification measure derived from diffusion MRI, which accounts for all possible neural pathways (direct and indirect) to quantify brain connectivity. We analyze data from the ADNI-2 and OASIS-3 datasets to derive relevant information for the study of the changes that the brain undergoes in AD.

引用

页码：591 / 595

页数：5

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