MR Compressed Sensing using FREBAS Transform

Satoshi Ito¹, Koji Miyabayashi, Yoshifumi Yamada

Compressed sensing (CS) aims to reconstruct signals and images from significantly fewer measurements than were traditionally thought necessary. MRI is a medical imaging tool burdened by an inherently slow data acquisition process. The application of CS to MRI has the potential for significant scan time reductions. In this paper we present a new CS method based on the FREBAS transform which we have proposed as a new kind of multi-resolution image analysis. The algorithm and the performances of proposed method were demonstrated and it was shown that proposed CS method can achieve a reduction factor higher than the standard CS method.