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Design D-optimal event-related functional magnetic resonance imaging experiments

机译:设计D最优事件相关功能磁共振成像实验

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摘要

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.
机译:提出了新的计算机算法,用于寻找功能性磁共振成像(MRI)实验的刺激序列的D最优设计。尽管通常通过线性模型来分析功能性MRI数据,但是功能性MRI设计矩阵的构造比传统的实验设计问题要复杂得多。受广泛使用的交换算法技术的启发,我们提出的方法在D功能优化设计的广阔功能性MRI设计空间上实现了贪婪搜索策略。与最近提出的遗传算法相比,我们的算法在计算时间方面更胜一筹,并且在单目标和多目标问题中均达到了设计效率。另外,所提出的算法足够灵活以在设计中包含要求每种刺激类型的精确出现次数的约束。不幸的是,现有方法无法很好地解决这个现实的设计问题。

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