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Cognitive decline in old age is tightly linked with brain atrophy, causing significant burden. It is critical to identify which biomarkers are most predictive of cognitive decline and brain atrophy in the elderly. In 566 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we used a novel unsupervised machine learning approach to evaluate an extensive list of more than 200 potential...
The Alzheimer's Disease Neuroimaging Initiative (ADNI) employed phantom-based scaling of T1-weighted MP-RAGE brain images to improve spatial calibration of scans and longitudinal stability across study sites. Early in ADNI, errors in phantom based scaling were identified due to incorrect acquisition protocols or replacement of phantoms. Images initially made available with questionable scaling factors...
There is an urgent need for neuroimaging biomarkers of Alzheimer's disease (AD) that correlate with cognitive decline, and with accepted measures of pathology detectable in cerebrospinal fluid (CSF). Ideal biomarkers should also be able to predict future decline, and should be computable automatically from hundreds to thousands of images without user intervention. Here we used our multi-atlas fluid...
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