Ultra-fast MRI of the human brain with simultaneous multi-slice imaging
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 …
dramatically reduced the scan time of the brain. The evolution of this parallel imaging …
[HTML][HTML] Challenges for biophysical modeling of microstructure
The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25
years. In this review, we dwell on the various challenges along the journey of bringing a …
years. In this review, we dwell on the various challenges along the journey of bringing a …
White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI
Diffusion-weighted MRI (DW-MRI) has been increasingly used in imaging neuroscience
over the last decade. An early form of this technique, diffusion tensor imaging (DTI) was …
over the last decade. An early form of this technique, diffusion tensor imaging (DTI) was …
Dipy, a library for the analysis of diffusion MRI data
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 …
of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an …
Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project
Abstract The Human Connectome Project (HCP) relies primarily on three complementary
magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging …
magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging …
QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data
Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for
noninvasively studying the organization of white matter in the human brain. Here we …
noninvasively studying the organization of white matter in the human brain. Here we …
Pushing the limits of in vivo diffusion MRI for the Human Connectome Project
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 …
from map** the major connection pathways in the living human brain with diffusion MRI …
Q-space deep learning: twelve-fold shorter and model-free diffusion MRI scans
Numerous scientific fields rely on elaborate but partly suboptimal data processing pipelines.
An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive …
An example is diffusion magnetic resonance imaging (diffusion MRI), a non-invasive …
A transfer‐learning approach for accelerated MRI using deep neural networks
Purpose Neural networks have received recent interest for reconstruction of undersampled
MR acquisitions. Ideally, network performance should be optimized by drawing the training …
MR acquisitions. Ideally, network performance should be optimized by drawing the training …
[HTML][HTML] DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning
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 …
microstructure and structural connectivity in the living human brain. Nonetheless, the …