Recently, the highly-constrained backprojection (HYPR) and HYPR with local reconstruction (HYPR LR) methods have been introduced to reconstruct magnitude images from a series of highly undersampled data while preserving high spatial and temporal resolution and high signal-to-noise ratio (SNR) in applications with spatiotemporal correlations. However, these conventional HYPR algorithms are limited to the generation of magnitude images and, therefore, have limitations in their potential applications. In this work, the HYPR LR algorithm has been modified to extend the use of algorithms in the HYPR family to applications that require processing of complex data, such as MR chemical shift imaging (CSI) or spectroscopic imaging. The proposed method processes the magnitude information the same way as in original HYPR LR processing. In addition, it improves the phase images by subtracting the phase map of a synthesized composite image. The feasibility and efficiency of this algorithm has been demonstrated on CSI of cortical bone, Achilles tendon, and a healthy volunteer on a clinical 3T scanner.
(c) 2009 Wiley-Liss, Inc.