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@ARTICLE{Orzada:163656,
author = {S. Orzada and T. M. Fiedler$^*$ and A. K. Bitz and M. E.
Ladd$^*$ and H. H. Quick},
title = {{L}ocal {SAR} compression with overestimation control to
reduce maximum relative {SAR} overestimation and improve
multi-channel {RF} array performance.},
journal = {Magnetic resonance materials in physics, biology and
medicine},
volume = {34},
number = {1},
issn = {1352-8661},
address = {Heidelberg},
publisher = {Springer},
reportid = {DKFZ-2020-01934},
pages = {153-163},
year = {2021},
note = {2021 Feb;34(1):153-163},
abstract = {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.},
cin = {E020},
ddc = {530},
cid = {I:(DE-He78)E020-20160331},
pnm = {315 - Bildgebung und Radioonkologie (POF4-315)},
pid = {G:(DE-HGF)POF4-315},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:32964299},
doi = {10.1007/s10334-020-00890-0},
url = {https://inrepo02.dkfz.de/record/163656},
}