Quantitative single point imaging with compressed sensing.
A novel approach with respect to single point imaging (SPI), compressed sensing, is presented here that is shown to significantly reduce the loss of accuracy of reconstructed images from under-sampled acquisition data. SPI complements compressed sensing extremely well as it allows unconstrained selection of sampling trajectories. Dynamic processes featuring short T2* NMR signal can thus be more rapidly imaged, in our case the absorption of moisture by a cereal-based wafer material, with minimal loss of image quantification. The absolute moisture content distribution is recovered via a series of images acquired with variable phase encoding times allowing extrapolation to time zero for each image pixel and the effective removal of T2* contrast.
Parasoglou
P
P
Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB2 3RA, UK.
Malioutov
D
D
Sederman
A J
AJ
Rasburn
J
J
Powell
H
H
Gladden
L F
LF
Blake
A
A
Johns
M L
ML
D000042:Absorption; D000465:Algorithms; D002523:Edible Grain / Q000737:chemistry; D004574:Electromagnetic Fields; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D014867:Water / Q000032:analysis
D014867:Water