Offset Sampling Improves Deep Learning based Accelerated MRI Reconstructions by Exploiting Symmetry

Code

• github.com/Kuga23/DL-fastMRI
  pytorch★ 1

Abstract

Deep learning approaches to accelerated MRI take a matrix of sampled Fourier-space lines as input and produce a spatial image as output. In this work we show that by careful choice of the offset used in the sampling procedure, the symmetries in k-space can be better exploited, producing higher quality reconstructions than given by standard equally-spaced samples or randomized samples motivated by compressed sensing.

Tasks

Reproductions