Voxel-based morphometry of the human brain: Methods and applications
By Andrea Mechelli, Cathy J. Price, Karl J. Friston, John Ashburner. 2005
898 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/bf65e48218b53af51805d33323b927315e686b19
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Citations in the corpus
- Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort (2010, methodology): “First, voxel-based morphometry (VBM; (Ashburner and Friston, 2000; Good et al., 2001; Mechelli et al., 2005)) was performed to define global grey matter (GM) density maps and extract local GM density values for 86 target regions (Table 1).”
- Deep ensemble learning of sparse regression models for brain disease diagnosis (2017, background): “One common way of minimizing such unexpected error is to normalize with the tissue-segmented images, instead of the whole-brain images ( Mechelli et al., 2005 ).”
- London taxi drivers and bus drivers: A structural MRI and neuropsychological analysis (2006, methodology): “Examination of magnetic resonance imaging (MRI) scans using whole-brain voxel-based morphometry (VBM; Ashburner and Friston, 2005; Mechelli et al., 2005) showed greater gray matter volume in the posterior hippocampi, and reduced anterior hippocampal gray matter volume in taxi drivers when compared w”
- How Does Your Cortex Grow? (2011, unknown): “Initially, cross-sectional studies established robust relationships between CV and factors such as age, sex, cognitive ability, and disease (Mechelli et al., 2005).”