Change Point Estimation of the Hippocampal Volumes in Alzheimer's Disease

被引：0

作者：

Tang, Xiaoying ^{[1
]}

Albert, Marilyn ^{[2
,3
]}

Miller, Michael I. ^{[2
,3
]}

Younes, Laurent ^{[2
,3
]}

机构：

[1] Sun Yat Sen Univ, CMU Joint Inst Engn, Guangzhou, Guangdong, Peoples R China

[2] Johns Hopkins Univ, Dept Neurol, Baltimore, MD USA

[3] Johns Hopkins Univ, Ctr Imaging Sci, Baltimore, MD USA

来源：

2016 13TH CONFERENCE ON COMPUTER AND ROBOT VISION (CRV) | 2016年

基金：

中国国家自然科学基金; 美国国家卫生研究院; 美国国家科学基金会;

关键词：

change point; maximum likelihood estimation; linear mixed-effects; Alzheimer's disease; hippocampus; MILD COGNITIVE IMPAIRMENT; DIFFEOMORPHOMETRY; AMYGDALA; ATROPHY;

D O I：

10.1109/CRV.2016.13

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

Volumetric changes in the hippocampus have been shown to precede clinical symptom onset during the preclinical phase of Alzheimer's disease (AD). In this paper, we propose a novel statistical method for estimating the change point of the hippocampus, as extracted from structural magnetic resonance imaging scans, in relation to clinical symptom onset. We used a linear mixed-effect statistical model. Maximum likelihood estimation was employed as the strategy that was applied in two phases.

引用

页码：358 / 361

页数：4

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