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Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance.
Magnetic Resonance Materials in Physics Biology and Medicine ( IF 2.3 ) Pub Date : 2020-09-22 , DOI: 10.1007/s10334-020-00890-0
Stephan Orzada 1, 2 , Thomas M Fiedler 3 , Andreas K Bitz 4 , Mark E Ladd 1, 3, 5, 6 , Harald H Quick 1, 2
Affiliation  

Objective

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.

Method

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.

Result

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.

Conclusion

The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission.



中文翻译:

具有高估控制的局部 SAR 压缩可减少最大相对 SAR 高估并提高多通道射频阵列性能。

客观的

在局部 SAR 压缩算法中,高估通常与实际局部 SAR 不是线性相关的。这会导致在低实际 SAR 值时相对过高估计,不必要地限制发射阵列性能。

方法

提出了两种策略来减少给定数量的 VOP 的最大相对高估。第一种策略使用高估矩阵,大致接近实际的局部 SAR;第二种策略使用一小组预先计算的 VOP 作为压缩的高估项。

结果

与先前方法的比较表明,对于给定的最大相对高估,VOP 的数量可以减少约 20%,但代价是在高实际局部 SAR 值时绝对高估更高。

结论

所提出的策略优于先前发布的策略,并且可以改善最大相对高估限制并行传输性能的 SAR 压缩。

更新日期:2020-09-22
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