Design D‐optimal event‐related functional magnetic resonance imaging experiments
Design D‐optimal event‐related functional magnetic resonance imaging experiments
复制标题
设计 D 最优事件相关功能磁共振成像实验
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
R. Pan
中科院分区：
文献类型：
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作者：
Moein Saleh;M. Kao;R. Pan
提出了一种新的用于功能磁共振成像(MRI)实验的激励序列D-最优设计的计算机算法。虽然功能磁共振成像数据通常采用线性模型进行分析，但功能磁共振成像设计矩阵的构造要比传统的实验设计问题复杂得多。受广泛使用的交换算法技术的启发，我们提出的方法在巨大的功能磁共振设计空间上实现了贪婪搜索策略，以求得到D-最优设计。与最近提出的遗传算法相比，该算法在计算时间上具有优势，在单目标和多目标问题上都达到了设计效率。此外，提出的算法足够灵活，可以包含一个约束，该约束要求设计中每种类型的刺激出现的确切数量。遗憾的是，现有方法并没有很好地处理这个现实的设计问题。
New computer algorithms for finding D‐optimal designs of stimulus sequence for functional magnetic resonance imaging (MRI) experiments are proposed. Although functional MRI data are commonly analysed by linear models, the construction of a functional MRI design matrix is much more complicated than in conventional experimental design problems. Inspired by the widely used exchange algorithm technique, our proposed approach implements a greedy search strategy over the vast functional MRI design space for a D‐optimal design. Compared with a recently proposed genetic algorithm, our algorithms are superior in terms of computing time and achieved design efficiency in both single‐objective and multiobjective problems. In addition, the algorithms proposed are sufficiently flexible to incorporate a constraint that requires the exact number of appearances of each type of stimulus in a design. This realistic design issue is unfortunately not well handled by existing methods.