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- W2124514449 abstract "Brain ventricle volume measured from high-resolution magnetic resonance imaging (MRI) is a sensitive measure of atrophy in subjects aging normally, those with mild cognitive impairment (MCI), or those with Alzheimer disease (AD). The purpose of this work was to develop a novel automated segmentation algorithm that increased the accuracy and precision of brain ventricle segmentation compared to existing methods allowing images to be processed quickly without bias. A novel algorithm was implemented that combined automated seed point placement with intensity texture-based fuzzy connectedness segmentation and shape-based Expectation Maximization (EM) segmentation. On occasions of leakage into the third and fourth ventricle, manual cropping was performed but will soon be replaced by automated cropping. The algorithm was initially validated using 3D T1-weighted MP-RAGE images of a realistic brain ventricle phantom. The algorithm was further tested in 25 normal elderly subjects, 19 subjects with MCI and 24 subjects with AD utilizing 1.5T T1-weighted MP-RAGE images acquired at baseline and 24 months. Subjects were randomly selected from the A lzheimer Disease Neuroimaging Initiative (ADNI) database. Change over time was determined by repeated measures ttest while differences between groups was determined by one-way ANOVA (P<0.05 considered significant). The brain ventricle phantom volume was determined within 0.8% of its known volume. Baseline ventricle volume (average ± SEM) was 35.3 ± 2.7 cm 3 for normal elderly, 46.0 ± 6.3 cm 3 for MCI and 50.3 ± 6.5 cm 3 for AD. A significant ventricle volume increase was detected over 24 months in MCI (P<0.001) and AD subjects (P<0.001), but not in normal elderly (P = 0.12). The incorporation of the EM segmentation increased ventricle volume by 5-6% due to inclusion of the temporal horn regions and increased the observed 24 month differences within groups by 22-90%." @default.
- W2124514449 created "2016-06-24" @default.
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- W2124514449 date "2012-07-01" @default.
- W2124514449 modified "2023-09-27" @default.
- W2124514449 title "IC-P-027: Tracking brain ventricle expansion in Alzheimer's disease using combined intensity and shape-based segmentation" @default.
- W2124514449 doi "https://doi.org/10.1016/j.jalz.2012.05.059" @default.
- W2124514449 hasPublicationYear "2012" @default.
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