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Automatic classification of patients with Alzheimer's disease from structural MRI: A comparison of ten methods using the ADNI database
TLDR
In this paper, we evaluated the performance of ten approaches (five voxel-based methods, three method based on cortical thickness and two methods based on the hippocampus) using 509 subjects from the ADNI database. Expand
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Support vector machine-based classification of Alzheimer’s disease from whole-brain anatomical MRI
PurposeWe present and evaluate a new automated method based on support vector machine (SVM) classification of whole-brain anatomical magnetic resonance imaging to discriminate between patients withExpand
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Fully automatic hippocampus segmentation and classification in Alzheimer's disease and mild cognitive impairment applied on data from ADNI
The hippocampus is among the first structures affected in Alzheimer's disease (AD). Hippocampal magnetic resonance imaging volumetry is a potential biomarker for AD but is hindered by the limitationsExpand
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Can voxel based morphometry, manual segmentation and automated segmentation equally detect hippocampal volume differences in acute depression?
TLDR
We compare the sensitivity of manual segmentation, automated segmentation and VBM to detect hippocampal structural changes in middle aged acute depressed population. Expand
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Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging
TLDR
We describe a new method to automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls, based on multidimensional classification of hippocampal shape features. Expand
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Structural connectivity differences in left and right temporal lobe epilepsy
TLDR
We performed whole brain connectome analysis in 39 patients with refractory temporal lobe epilepsy and unilateral hippocampal sclerosis (20 right and 19 left) and 28 healthy subjects. Expand
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Discrimination between Alzheimer disease, mild cognitive impairment, and normal aging by using automated segmentation of the hippocampus.
PURPOSE To prospectively evaluate the accuracy of automated hippocampal volumetry to help distinguish between patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), andExpand
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Automatic segmentation of the hippocampus and the amygdala driven by hybrid constraints: Method and validation
TLDR
The segmentation from MRI of macroscopically ill-defined and highly variable structures, such as the hippocampus (Hc) and the amygdala (Am), requires the use of specific constraints. Expand
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Early and protective microglial activation in Alzheimer's disease: a prospective study using 18F-DPA-714 PET imaging.
While emerging evidence suggests that neuroinflammation plays a crucial role in Alzheimer's disease, the impact of the microglia response in Alzheimer's disease remains a matter of debate. We aimedExpand
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Basal temporal sulcal morphology in healthy controls and patients with temporal lobe epilepsy
Background: We previously demonstrated that shape variants of the hippocampal formation are more prevalent in patients with temporal lobe epilepsy (TLE) than in healthy individuals. Objective: ToExpand
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