Compressed Sensing for Thoracic MRI with Partial Random Circulant Matrices
Abstract: The use of circulant
matrix as the sensing matrix in compressed sensing (CS) scheme has recently
been proposed to overcome the limitation of random or partial Fourier matrices.
Aside from reducing computational complexity, the use of circulant matrix for
magnetic resonance (MR) image offers the feasibility in hardware
implementations. This paper presents the simulation of compressed sensing for
thoracic MR imaging with circulant matrix as the sensing matrix. The comparisons
of reconstruction of three different type MR images using circulant matrix are
investigated in term of number of samples, number of iteration and signal to
noise ratio (SNR). The simulation results showed that circulant matrix works
efficiently for encoding the MR image of respiratory organ, especially for
smooth and sparse image in spatial domain.
Author: Windra Swastika,
Hideaki Haneishi
Journal Code: jptkomputergg120035