We have shown that MultiNet, a neural-network-based image reconstruction, can reconstruct variable-density k-space undersampling schemes to decrease MRSI acquisition times. This used a 4-step method where points are predicted by 4 successively-applied neural-networks off both acquired and previously predicted k-space points. Herein, a 1-step method where points are only predicted off acquired k-space points to reduce reconstruction error was explored. This method was trained using a new augmented MRSI training set and compared to the 4-step reconstruction of new CAIPIRINHA-based schemes and the original schemes. The new 1-step reconstruction method was found to increase SNR and improve metabolic maps.
This abstract and the presentation materials are available to members only; a login is required.