Knutsson Hans, Westin Carl-Fredrik
Med Image Comput Comput Assist Interv. 2014;17(Pt 3):217-24. doi: 10.1007/978-3-319-10443-0_28.
We present a novel approach to determine a local q-space metric that is optimal from an information theoreticperspective with respect to the expected signal statistics. It should be noted that the approach does not attempt to optimize the quality of a pre-defined mathematical representation, the estimator. In contrast, our suggestion aims at obtaining the maximum amount of information without enforcing a particular feature representation. Results for three significantly different average propagator distributions are presented. The results show that the optimal q-space metric has a strong dependence on the assumed distribution in the targeted tissue. In many practical cases educated guesses can be made regarding the average propagator distribution present. In such cases the presented analysis can produce a metric that is optimal with respect to this distribution. The metric will be different at different q-space locations and is defined by the amount of additional information that is obtained when adding a second sample at a given offset from a first sample. The intention is to use the obtained metric as a guide for the generation of specific efficient q-space sample distributions for the targeted tissue.
我们提出了一种新颖的方法来确定局部q空间度量，该度量从信息论角度来看，相对于预期信号统计量是最优的。应当指出的是，该方法并非试图优化预定义数学表示（即估计器）的质量。相反，我们的建议旨在在不强制特定特征表示的情况下获取最大信息量。文中给出了三种显著不同的平均传播子分布的结果。结果表明，最优q空间度量强烈依赖于目标组织中假定的分布。在许多实际情况下，可以对存在的平均传播子分布进行有根据的猜测。在这种情况下，所提出的分析可以产生相对于该分布而言最优的度量。该度量在不同的q空间位置会有所不同，并且由在距第一个样本给定偏移处添加第二个样本时所获得的额外信息量来定义。目的是将获得的度量用作生成目标组织特定有效q空间样本分布的指导。
