Optimal k-space sampling for single point imaging of transient systems

Abstract

A modification of the Single Point Imaging (SPI) is presented. The novel approach aims at increasing the sensitivity of the method and hence the resulting Signal-to-Noise ratio (SNR) for a given total time interval. With prior knowledge of the shape of the object under study, a selective sparse k-space sampling can then be used to follow dynamic phenomena of transient systems, in this case the absorption of moisture by a cereal-based wafer material. Further improvement in the image quality is achieved when the un-sampled k-space points are replaced by those of the initial dry or the final wet sample acquired at the beginning and the end of the acquisition respectively when there are no acquisition time limitations.