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Optimal Radiofrequency Pulse Design for Magnetic Resonance Imaging Using Genetic Algorithms

机译:遗传算法磁共振成像的最佳射频脉冲设计

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The proper design of RF pulses in magnetic resonance imaging (MRI) has a direct impact on the quality of acquired images, and is needed for many applications. Several techniques have been proposed to obtain the RF pulse envelope given the desired slice profile. Unfortunately, these techniques do not take into account the limitations of practical implementation such as limited amplitude resolution. Moreover, implementing constraints for special RF pulses on most techniques are not possible. In this work, an approach is proposed to develop for designing optimal RF pulses under theoretically any constraints. The new technique poses the RF pulse design problem as a combinatorial optimization problem and uses efficient techniques from this area such as genetic algorithms (GA) to solve this problem. In particular, an objective function is proposed as the norm of the difference between the desired profile and the one obtained from solving the Bloch equations for the current RF pulse design values. The proposed approach is verified using analytical solution based RF simulations and compared to previous methods such as Shinnar-Le Roux (SLR) method, and analysis, selected, and tested the options and parameters that control the Genetic Algorithm (GA) can significantly affect its performance to get the best improved results. The results show a significant improvement over conventional design techniques, and suggest the practicality of using of the new technique for most important applications as slice selection for large flip angles, in the area of unconventional spatial encoding, and another clinical use.
机译:磁共振成像(MRI)中的RF脉冲的正确设计对所获取的图像的质量有直接影响,并且对于许多应用来说是所需的。已经提出了几种技术以获得所需切片曲线的RF脉冲包络。不幸的是,这些技术没有考虑到实际实现的局限性,例如有限的幅度分辨率。此外,对于大多数技术而言,对特殊RF脉冲的限制是不可能的。在这项工作中,提出了一种方法来开发在理论上在理论上设计最佳RF脉冲。新技术将RF脉冲设计问题构成为组合优化问题,并利用来自该区域的有效技术,例如遗传算法(GA)来解决这个问题。特别地,提出了一种目标函数作为所需轮廓和从求解电流RF脉冲设计值的BLOC方程而获得的差异的标准。使用基于分析解决方案的RF模拟验证所提出的方法,并与先前的方法(如Shinnar-Le Roux(SLR)方法)进行比较,以及分析,选择和测试控制遗传算法(GA)的选项和参数,可以显着影响其表现获得最佳改进的结果。结果表现出对传统设计技术的显着改进,并提出了使用新技术的实用性作为大多数重要应用,作为大型翻转角度的切片选择,在非传统的空间编码和另一种临床用途中。

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