OEDIPUS：稀疏约束MRI的实验设计框架
OEDIPUS: An Experiment Design Framework for Sparsity-Constrained MRI
摘要：
本文介绍了一种新的估计理论框架的实验设计的背景下，稀疏约束下的MR图像重建。新的框架被称为OEDIPUS（基于Oracle的实验设计成像稀疏约束下的吝啬），是基于结合约束的Cramér-Rao界与经典的实验设计技术。与流行的随机采样方法相比，OEDIPUS是完全确定性的，并且自动将采样模式调整到感兴趣的特定成像环境（即，考虑线圈几何形状、解剖结构、图像对比度等）。基于OEDIPUS的实验设计在几种不同的情况下使用回顾性二次采样的体内MRI数据进行评估。结果表明，OEDIPUS为基础的实验设计有一些可取的特点，相对于传统的MRI采样方法。
英文摘要：
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. Results demonstrate that OEDIPUS-based experiment designs have some desirable characteristics relative to conventional MRI sampling approaches.
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