Myelin Water Fraction Estimation Using Small-Tip Fast Recovery MRI

Steven T. Whitaker, Gopal Nataraj, Jon-Fredrik Nielsen, Jeffrey A. Fessler

# Overview
In this work, we optimized the scan parameters for a set of small-tip fast
recovery (STFR) MRI scans for estimating myelin water fraction (MWF).
The scans were optimized to minimize the Cramer-Rao Lower Bound (CRLB)
(or maximize the precision) of estimates of MWF. The optimized scans
were used to acquire an in vivo dataset, from which we estimated MWF using
parameter estimation via regression with kernels (PERK) using a
three-compartment tissue model with exchange. The STFR-based MWF estimates
were compared to multi-echo spin echo (MESE) MWF estimates obtained using
non-negative least squares (NNLS). The STFR-based MWF estimates were similar
to the MESE-based estimates, but were much less noisy.

# About This Repository
This repository contains the raw scan data from the in vivo scans. It also
contains the reconstructed images for the single slice we analyzed in the
paper, as well as data files for separately estimated parameters and binary
masks. See the detailed description for links to code repositories that can be
used to work with the data. In particular, look at the README for
https://github.com/StevenWhitaker/STFR-MWF for step-by-step instructions for
how to reproduce the results in the paper.