A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
A Regularized MRI Image Reconstruction based on Hessian Penalty Term on CPU/GPU Systems
2013
Procedia Computer Science
In this paper we investigate an inverse reconstruction problem of Magnetic Resonance Imaging with few acquired body scanner samples. The missing information in the Fourier domain causes image artefacts, therefore iterative computationally expensive recovery techniques are needed. We propose a regularization approach based on second order derivative of both simulated and real images with highly undersampled data, obtaining a good reconstruction accuracy. Moreover, an accelerated regularization
doi:10.1016/j.procs.2013.06.001
fatcat:olmjjgzgdjd25ko2md2763ysja