Journal Article

DKFZ-2020-02464

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Compressed sensing and the use of phased array coils in 23Na MRI: a comparison of a SENSE-based and an individually combined multi-channel reconstruction.

Lachner, S. ; Utzschneider, M. ; Zaric, O. ; Minarikova, L. ; Ruck, L. ; Zbýň, Š. ; Hensel, B. ; Trattnig, S. ; Uder, M. ; Nagel, A. (Last author)DKFZ*

2021
Elsevier, Urban & Fischer45882 Amsterdam

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Please use a persistent id in citations: doi:10.1016/j.zemedi.2020.10.003

Abstract: To implement and to evaluate a compressed sensing (CS) reconstruction algorithm based on the sensitivity encoding (SENSE) combination scheme (CS-SENSE), used to reconstruct sodium magnetic resonance imaging (23Na MRI) multi-channel breast data sets.In a simulation study, the CS-SENSE algorithm was tested and optimized by evaluating the structural similarity (SSIM) and the normalized root-mean-square error (NRMSE) for different regularizations and different undersampling factors (USF=1.8/3.6/7.2/14.4). Subsequently, the algorithm was applied to data from in vivo measurements of the healthy female breast (n=3) acquired at 7T. Moreover, the proposed CS-SENSE algorithm was compared to a previously published CS algorithm (CS-IND).The CS-SENSE reconstruction leads to an increased image quality for all undersampling factors and employed regularizations. Especially if a simple 2nd order total variation is chosen as sparsity transformation, the CS-SENSE reconstruction increases the image quality of highly undersampled data sets (CS-SENSE: SSIMUSF=7.2=0.234, NRMSEUSF=7.2=0.491 vs. CS-IND: SSIMUSF=7.2=0.201, NRMSEUSF=7.2=0.506).The CS-SENSE reconstruction supersedes the need of CS weighting factors for each channel as well as a method to combine single channel data. The CS-SENSE algorithm can be used to reconstruct undersampled data sets with increased image quality. This can be exploited to reduce total acquisition times in 23Na MRI.

Note: #LA:E020#2021 Feb;31(1):48-57

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Contributing Institute(s):

1. E020 Med. Physik in der Radiologie (E020)

Research Program(s):

1. 315 - Bildgebung und Radioonkologie (POF4-315) (POF4-315)

Appears in the scientific report 2021

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Database coverage:
; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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