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