  This paper introduces a new estimation-theoretic framework for experiment
design in the context of MR image reconstruction under sparsity constraints.
The new framework is called OEDIPUS (Oracle-based Experiment Design for Imaging
Parsimoniously Under Sparsity constraints), and is based on combining the
constrained Cram\'{e}r-Rao bound with classical experiment design techniques.
Compared to popular random sampling approaches, OEDIPUS is fully deterministic
and automatically tailors the sampling pattern to the specific imaging context
of interest (i.e., accounting for coil geometry, anatomy, image contrast,
etc.). OEDIPUS-based experiment designs are evaluated using retrospectively
subsampled in vivo MRI data in several different contexts. Results demonstrate
that OEDIPUS-based experiment designs have some desirable characteristics
relative to conventional MRI sampling approaches.
