Microstructure imaging seeks to noninvasively measure and map microscopic tissue
features by pairing mathematical modeling with tailored MRI protocols. This article reviews …

This paper introduces a new estimationtheoretic framework for experiment design in the
context of MR image reconstruction under sparsity constraints. The new framework is called …

We introduce and demonstrate an unsupervised machine learning technique for
spectroscopic analysis of quantitative MRI experiments. Our algorithm supports estimation of …

Background Renal interstitial fibrosis is one of the most common pathways in the
progression of chronic kidney disease (CKD). Noninvasive evaluation of interstitial fibrosis …

Quantitative assessment of brain myelination has gained attention for both research and
diagnosis of neurological diseases. However, conventional pulse sequences cannot directly …

Multiexponential modeling of relaxation or diffusion MR signal decays is a popular approach
for estimating and spatially mapping different microstructural tissue compartments. While this …

Multi-dimensional diffusion–relaxation correlation (DRC) magnetic resonance imaging (MRI)
techniques have recently been developed to investigate tissue microstructures. Sub-voxel …

NMR relaxometry can provide information about the relaxation of the magnetization in
different tissues, increasing our understanding of molecular dynamics and biochemical …

We introduce and demonstrate an unsupervised machine learning method for spectroscopic
analysis of quantitative MRI (qMRI) experiments. qMRI data can support estimation of …

Synopsis T Relaxation-T Relaxation Correlation Spectroscopic Imaging (RR-CSI) is a novel
multidimensional imaging approach that estimates a 2D TT correlation spectrum at every …