Quantitative single point imaging with compressed sensing.

Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB2 3RA, UK.
Journal of Magnetic Resonance (Impact Factor: 2.3). 09/2009; 201(1):72-80. DOI: 10.1016/j.jmr.2009.08.003
Source: PubMed

ABSTRACT 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.

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