MRI reconstruction via non-convex total variation regularization
The demos implement the experiments given in the paper "Magnetic Resonance Imaging reconstruction via non-convex total variation regularization (MCTV_L2)".
After unzipping the supplementary file, please add all sub-directories into your MATLAB paths.
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'main.m' give a simple example to illustrate the efficiency of MCTV_L2.
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'rec_mctv2.m' and 'shrink_mctv2_1.m' are the main part of MCTV_L2.
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'rec_mctv.m' and 'shrink_mctv.m' are from paper "Convex MR brain image reconstruction via non-convex total variation minimization" by Liu et.al..
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'mask_radial.m' is used to generate radial sampling templates. Template size and number of trajectory lines can be chosen.
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'mask_random.m' is used to generate random sampling templates.
genPDF.m
andgengenSampling.m
are subroutines ofmask_random.m
(© 2007 Michael Lustig). Template size, sampling radius and sampling rate can be chosen. -
'mask_Cartesian.m' is used to generate Cartesian templates. Template size and number of readout lines can be chosen.
Constacts: zoujian@yangtzeu.edu.cn