Evidence map›Paper›PMID 33957210›Full record

ArticleMagnetic resonance imaging2021

Real-time dynamic vocal tract imaging using an accelerated spiral GRE sequence and low rank plus sparse reconstruction.

Xue Feng, Zhixing Wang, Craig H Meyer

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Article in Magnetic resonance imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Xue FengDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA. Electronic address: xf4j@virginia.edu.
Zhixing WangDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Craig H MeyerDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA; Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA.

Funding

Motion-Robust Methods for Rapid Pediatric MRI without SedationR21EB022309 · NIBIB · UNIVERSITY OF VIRGINIA · PI MEYER, CRAIG H · 2016 to 2018
$539k
NIBIB NIH HHS R21 EB022309
6 · The paper itself

Abstract

purposeTo develop a real-time dynamic vocal tract imaging method using an accelerated spiral GRE sequence and low rank plus sparse reconstruction.

methodsSpiral k-space sampling has high data acquisition efficiency and thus is suited for real-time dynamic imaging; further acceleration can be achieved by undersampling k-space and using a model-based reconstruction. Low rank plus sparse reconstruction is a promising method with fast computation and increased robustness to global signal changes and bulk motion, as the images are decomposed into low rank and sparse terms representing different dynamic components. However, the combination with spiral scanning has not been well studied. In this study an accelerated spiral GRE sequence was developed with an optimized low rank plus sparse reconstruction and compared with L1-SPIRiT and XD-GRASP methods. The off-resonance was also corrected using a Chebyshev approximation method to reduce blurring on a frame-by-frame basis.

resultsThe low rank plus sparse reconstruction method is sensitive to the weights of the low rank and sparse terms. The optimized reconstruction showed advantages over other methods with reduced aliasing and improved SNR. With the proposed method, spatial resolution of 1.3*1.3 mm

conclusionThis work studies low rank plus sparse reconstruction using the spiral trajectory and demonstrates a new method for dynamic vocal tract imaging which can benefit studies of speech disorders.

Indexed as

Image Processing, Computer-AssistedMagnetic Resonance ImagingAlgorithmsHumansMotionLow rank plus sparseOff-resonance correctionReal-time vocal tract imagingSpiral

Identifiers

PMID33957210
PMCPMC8169591

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