Magnetic resonance imaging and computed tomography from multiple batches (eg sites,
scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to …

Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron
emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches …

All fields of neuroscience that employ brain imaging need to communicate their results with
reference to anatomical regions. In particular, comparative morphometry and group analysis …

Automatic whole-brain extraction from magnetic resonance images (MRI), also known as
skull stripping, is a key component in most neuroimage pipelines. As the first element in the …

While computed tomography and other imaging techniques are measured in absolute units
with physical meaning, magnetic resonance images are expressed in arbitrary units that are …

We introduce an optimised pipeline for multi-atlas brain MRI segmentation. Both accuracy
and speed of segmentation are considered. We study different similarity measures used in …

Intensity normalization is an important pre-processing step in the study and analysis of
Magnetic Resonance Images (MRI) of human brains. As most parametric supervised …

Modern neuroimaging studies frequently combine data collected from multiple scanners and
experimental conditions. Such data often contain substantial technical variability associated …

Simple Summary As magnetic resonance (MR) intensities are acquired in arbitrary units,
scans from different scanners are not directly comparable; thus, intensity normalization is …

Accuracy of the results obtained by automated processing of brain magnetic resonance
images has vital importance for diagnosis and evaluation of a progressive disease during …