Improved Quantitative Susceptibility Mapping with Weighted Total Least Squares
Matlab Codes:
#Matlab Implementation of Weighted Total Least Squares Algorithm (proposed):
Phantom simulations: Generate_Fig1.m
Generate_Fig2.m
Generate_Fig3.m (requires various_snr.m)
Generate_Fig4.m
Generate_Fig5.m
Generate_Fig6.m
requires ---- data can be downloaded from: http://weill.cornell.edu/mri/pages/qsm.html
qsm_lttls.m
ttls_my.m
sparse_tv_qsm.m
addNoise.m
compute_rmse.m
compute_hfen.m
compute_ssim.m
viewOrthoSlices2D_phantom_view.m
in vivo simulations: Generate_Fig7.m
requires ---- data can be downloaded from: http://www.neuroimaging.at/qsm2016/pages/qsm-challenge.php
viewOrthoSlices2D_myrealnew.m
The data obtained after adding noise to the numerical phantom cases to test TLS methods were shared in the following link:
https://drive.google.com/open?id=0B2HqXYSU1ttaOXhfcENYQ2ROU2c
#Matlab Implementation of LSQR, L2, and L1 Algorithm:
Available in:
J.Chung, L.Ruthotto, "Computational Methods for Image Reconstruction", (http://dx.doi.org/10.1002/nbm.3545), NMR Biomedicine Special Issue: QSM, 2016.
This Matlab code is used as part of the work presented in:
Sreedevi Gutta, Venkata Suryanarayana Kadimesetty, and Phaneendra K. Yalavarthy, “Improved Quantitative Susceptibility Mapping with Weighted Total Least Squares," Magnetic Resonance in Medicine (Submitted).
Created on: Dec 22, 2016
Modified on: May 29, 2017