Physiological properties of tumors can be measured both in vivo and noninvasively by
diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic resonance imaging …

Early evaluation of treatment response and prediction of disease evolution are key issues in
the management of people with multiple sclerosis (MS). In the past 20 years, MRI has …

Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability
to identify meaningful biomarkers is limited by measurement reliability; unreliable measures …

Mindboggle (http://mindboggle. info) is an open source brain morphometry platform that
takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data …

Whole brain segmentation from structural magnetic resonance imaging (MRI) is a
prerequisite for most morphological analyses, but is computationally intense and can …

Abstract Introduction The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued
development and standardization of methodologies for biomarkers and has provided an …

Positive associations between human intelligence and brain size have been suspected for
more than 150 years. Nowadays, modern non-invasive measures of in vivo brain volume …

The reconstruction of cortical surfaces from brain magnetic resonance imaging (MRI) scans
is essential for quantitative analyses of cortical thickness and sulcal morphology. Although …

Metrics of brain morphology are increasingly being used to examine inter-individual
differences, making it important to evaluate the reliability of these structural measures. Here …

Quality control of brain segmentation is a fundamental step to ensure data quality. Manual
quality control strategies are the current gold standard, although these may be unfeasible for …