The recent advancement of simultaneous multi-slice imaging using multiband excitation has
dramatically reduced the scan time of the brain. The evolution of this parallel imaging …

The key component of a microstructural diffusion MRI 'super-scanner'is a dedicated high-
strength gradient system that enables stronger diffusion weightings per unit time compared …

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis
of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an …

Abstract The Human Connectome Project (HCP) relies primarily on three complementary
magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging …

Numerous scientific fields rely on elaborate but partly suboptimal data processing pipelines.
An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive …

Perhaps more than any other “-omics” endeavor, the accuracy and level of detail obtained
from map** the major connection pathways in the living human brain with diffusion MRI …

Diffusion-weighted magnetic resonance imaging (DWI) is the only non-invasive method for
quantifying microstructure and reconstructing white-matter pathways in the living human …

Diffusion tensor magnetic resonance imaging (DTI) is unsurpassed in its ability to map tissue
microstructure and structural connectivity in the living human brain. Nonetheless, the …

Diffusion magnetic resonance imaging (MRI) is a standard imaging tool in clinical neurology,
and is becoming increasingly important for neuroscience studies due to its ability to depict …

Purpose We introduce L2‐regularized reconstruction algorithms with closed‐form solutions
that achieve dramatic computational speed‐up relative to state of the art L1‐and L2‐based …