Improved algorithms for image reconstruction from sensitivity encoded data

Parallel magnetic resonance imaging through sensitivity encoding using multiple receiver coils has emerged as an effective tool to reduce imaging time. However, errors in both the estimated coil sensitivity maps and the measured data, and the ill-conditioned nature of the coefficient matrix (often associated with non-localized coils) can degrade image quality significantly, limiting speed enhancements. This paper addresses this problem using wavelet denoising and advanced regularization methods.