IEEE Trans Med Imaging. 2019 Jul;38(7):1545-1558. doi: 10.1109/TMI.2019.2896180. Epub 2019 Feb 1.
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 Cramér-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. The results demonstrate that OEDIPUS-based experiment designs have some desirable characteristics relative to conventional MRI sampling approaches.
本文提出了一种新的基于约束最大似然估计的稀疏磁共振图像重建实验设计框架。该框架称为 OEDIPUS（基于约束的稀疏约束下成像的实验设计），它基于将约束克拉美-罗界与经典实验设计技术相结合。与流行的随机采样方法相比，OEDIPUS 是完全确定性的，并自动根据特定的成像背景（即考虑线圈几何形状、解剖结构、图像对比度等）来调整采样模式。使用不同背景下的体内 MRI 数据进行了基于 OEDIPUS 的实验设计的评估。结果表明，与传统的 MRI 采样方法相比，基于 OEDIPUS 的实验设计具有一些理想的特性。
