Nonlinear registration of longitudinal images and measurement of change in regions of interest

被引:96
|
作者
Holland, Dominic [1 ,2 ]
Dale, Anders M. [1 ,2 ,3 ]
机构
[1] Univ Calif San Diego, Multimodal Imaging Lab, La Jolla, CA 92037 USA
[2] Univ Calif San Diego, Dept Neurosci, La Jolla, CA 92037 USA
[3] Univ Calif San Diego, Dept Radiol, La Jolla, CA 92037 USA
基金
美国国家卫生研究院;
关键词
Nonlinear image registration; Regional change quantification and visualization; MRI biomarkers; MILD COGNITIVE IMPAIRMENT; TENSOR-BASED MORPHOMETRY; SURFACE-BASED ANALYSIS; ALZHEIMERS-DISEASE; MR-IMAGES; BRAIN ATROPHY; VOLUME; SEGMENTATION; PREDICTION; DISORDERS;
D O I
10.1016/j.media.2011.02.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We describe here a method, Quarc, for accurately quantifying structural changes in organs, based on serial MRI scans. The procedure can be used to measure deformations globally or in regions of interest (ROls), including large-scale changes in the whole organ, and subtle changes in small-scale structures. We validate the method with model studies, and provide an illustrative analysis using the brain. We apply the method to the large, publicly available ADNI database of serial brain scans, and calculate Cohen's d effect sizes for several ROls. Using publicly available derived-data, we directly compare effect sizes from Quarc with those from four existing methods that quantify cerebral structural change. Quarc produced a slightly improved, though not significantly different, whole brain effect size compared with the standard KN-BSI method, but in all other cases it produced significantly larger effect sizes. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:489 / 497
页数:9
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