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Magnetic Resonance in Medicine
Article . 2014 . Peer-reviewed
License: Wiley Online Library User Agreement
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SENSE and simultaneous multislice imaging

Authors: Zahneisen, B.; Ernst, T.; Poser, B.A.;

SENSE and simultaneous multislice imaging

Abstract

PurposeSimultaneous multislice (SMS) acquisitions play an important role in the challenge of increasing single‐shot imaging speed. We show that sensitivity encoding in two spatial dimensions (two‐dimensional sensitivity encoding [2D‐SENSE]) can be used to reconstruct SMS acquisitions with periodic but otherwise arbitrary undersampling patterns.Theory and MethodsBy adopting a 3D k‐space representation of the SMS sampling process, the accelerated in‐plane and slice‐encoding directions form a 2D‐reconstruction problem that is equivalent to volumetric controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA). 2D‐SENSE does not otherwise distinguish between standard volumetric and SMS imaging with arbitrary CAIPIRINHA sampling.ResultsUse of the SENSE algorithm is demonstrated for in vivo brain data obtained with blipped‐CAIPRINHA sampling in 2D SMS‐echo planar imaging (EPI) and rapid acquisition with relaxation enhancement (RARE) acquisitions as well as 3D‐EPI with various in‐plane and through‐plane acceleration factors and CAIPIRINHA shifts. The proposed SENSE reconstruction works for any combination of SMS‐factor and CAIPIRINHA shift by the addition of “dummy slices” that allow for noninteger undersampling in the slice direction. Images with commonly used slice‐generalized autocalibrating partially parallel acquisitions reconstruction are shown for reference.ConclusionSENSE is conceptually simple and provides a one‐step reconstruction along both undersampled dimensions. It also provides a contrast‐independent parallel imaging reconstruction for SMS. Magn Reson Med 74:1356–1362, 2015. © 2014 Wiley Periodicals, Inc.

Country
Netherlands
Keywords

Echo-Planar Imaging, Image Processing, Computer-Assisted, Brain, Humans, Signal Processing, Computer-Assisted, Signal-To-Noise Ratio, Algorithms, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
58
Top 10%
Top 10%
Top 10%
hybrid