SVD Eigenimage Based SENSE

Yu Li¹, Feng Huang¹, Wei Lin¹, Charlie Saylor¹, Arne Reykowski¹

In this study, an eigenimage theory was developed for SENSE. Using singular value decomposition (SVD), the full FOV image can be reconstructed by summing several eigenimages weighted by some coefficients calculated from the eigenvalues of a sensitivity matrix. Based on this theory, a data-driven regularization technique was proposed to overcome the challenges of inaccurate sensitivity maps and noise amplification in SENSE reconstruction. This is a new technique that can offer simplicity and efficiency in SENSE g-factor control and artifact suppression.