Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Kokereiallee 7, 45141, Essen, Germany.
High-Field and Hybrid MR Imaging, University Hospital Essen, 45147, Essen, Germany.
MAGMA. 2021 Feb;34(1):153-163. doi: 10.1007/s10334-020-00890-0. Epub 2020 Sep 22.
In local SAR compression algorithms, the overestimation is generally not linearly dependent on actual local SAR. This can lead to large relative overestimation at low actual SAR values, unnecessarily constraining transmit array performance.
Two strategies are proposed to reduce maximum relative overestimation for a given number of VOPs. The first strategy uses an overestimation matrix that roughly approximates actual local SAR; the second strategy uses a small set of pre-calculated VOPs as the overestimation term for the compression.
Comparison with a previous method shows that for a given maximum relative overestimation the number of VOPs can be reduced by around 20% at the cost of a higher absolute overestimation at high actual local SAR values.
The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission.
在局部比吸收率（SAR）压缩算法中，通常不会将高估值与实际局部 SAR 线性相关。这可能导致在实际 SAR 值较低时出现较大的相对高估，从而不必要地限制发射阵列的性能。
提出了两种策略来降低给定数量的视频对象平面（VOP）的最大相对高估。第一种策略使用大致近似实际局部 SAR 的高估矩阵；第二种策略则使用一小部分预计算的 VOP 作为压缩的高估项。
与之前的方法相比，对于给定的最大相对高估，可以在不增加绝对高估的情况下，将 VOP 的数量减少约 20%，前提是在实际局部 SAR 值较高时。
所提出的策略优于之前发表的策略，可以改善在最大相对高估限制并行传输性能的情况下的 SAR 压缩。
