TITLE:
Comparison of MRI Under-Sampling Techniques for Compressed Sensing with Translation Invariant Wavelets Using FastTestCS: A Flexible Simulation Tool
AUTHORS:
Christopher Baker
KEYWORDS:
Compressed Sensing, Translation Invariant Wavelet, Simulation Software, Total Variation l1 Minimization
JOURNAL NAME:
Journal of Signal and Information Processing,
Vol.7 No.4,
November
22,
2016
ABSTRACT: A sparsifying transform for use in
Compressed Sensing (CS) is a vital piece of image reconstruction for Magnetic
Resonance Imaging (MRI). Previously, Translation Invariant Wavelet Transforms
(TIWT) have been shown to perform exceedingly well in CS by reducing repetitive
line pattern image artifacts that may be observed when using orthogonal
wavelets. To further establish its validity as a good sparsifying transform,
the TIWT is comprehensively investigated and compared with Total Variation
(TV), using six under-sampling patterns through simulation. Both trajectory and
random mask based under-sampling of MRI data are reconstructed to demonstrate a
comprehensive coverage of tests. Notably, the TIWT in CS reconstruction
performs well for all varieties of under-sampling patterns tested, even for
cases where TV does not improve the mean squared error. This improved Image
Quality (IQ) gives confidence in applying this transform to more CS
applications which will contribute to an even greater speed-up of a CS MRI
scan. High vs low resolution time of flight MRI CS re-constructions are also
analyzed showing how partial Fourier acquisitions must be carefully addressed
in CS to prevent loss of IQ. In the spirit of reproducible research, novel
software is introduced here as FastTestCS. It is a helpful tool to quickly
develop and perform tests with many CS customizations. Easy integration and
testing for the TIWT and TV minimization are exemplified. Simulations of 3D MRI
datasets are shown to be efficiently distributed as a scalable solution for
large studies. Comparisons in reconstruction computation time are made between
the Wavelab toolbox and Gnu Scientific Library in FastTestCS that show a
significant time savings factor of 60×. The addition of FastTestCS is proven to
be a fast, flexible, portable and reproducible simulation aid for CS research.