Selection of observations in magnetic resonance spectroscopic imaging

Magnetic resonance spectroscopic imaging (MRSI) is a type of MRI in which both spatial and spectral information are gathered. Unfortunately, the time required to acquire a high-resolution image is prohibitive. Thus, we desire to gather the most informative data possible in the limited time available. The particular choice of a limited set of k-space samples has a tremendous impact on the quality of the reconstructed image. In previous work, we demonstrated a technique for choosing k-space samples under the assumption of a least-squares reconstruction given knowledge of the region of support of the image. In this work, we extend our criterion to a Wiener filter reconstruction. Furthermore, we exploit the properties of the Wiener filter criterion to derive a new optimization strategy. This optimization strategy allows us to begin the k-space acquisition process before the choice of k-space samples is complete. Results are demonstrated on an acquired MRI phantom.