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Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance
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 ma...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910258/ https://www.ncbi.nlm.nih.gov/pubmed/32964299 http://dx.doi.org/10.1007/s10334-020-00890-0 |
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author | Orzada, Stephan Fiedler, Thomas M. Bitz, Andreas K. Ladd, Mark E. Quick, Harald H. |
author_facet | Orzada, Stephan Fiedler, Thomas M. Bitz, Andreas K. Ladd, Mark E. Quick, Harald H. |
author_sort | Orzada, Stephan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7910258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-79102582021-03-15 Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance Orzada, Stephan Fiedler, Thomas M. Bitz, Andreas K. Ladd, Mark E. Quick, Harald H. MAGMA Research Article 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. Springer International Publishing 2020-09-22 2021 /pmc/articles/PMC7910258/ /pubmed/32964299 http://dx.doi.org/10.1007/s10334-020-00890-0 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Article Orzada, Stephan Fiedler, Thomas M. Bitz, Andreas K. Ladd, Mark E. Quick, Harald H. Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance |
title | Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance |
title_full | Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance |
title_fullStr | Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance |
title_full_unstemmed | Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance |
title_short | Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance |
title_sort | local sar compression with overestimation control to reduce maximum relative sar overestimation and improve multi-channel rf array performance |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910258/ https://www.ncbi.nlm.nih.gov/pubmed/32964299 http://dx.doi.org/10.1007/s10334-020-00890-0 |
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