NDLI: Highly Undersampled Magnetic Resonance Image Reconstruction via Homotopic <formula formulatype=inline><tex Notation=TeX>$ell

Content Provider	IEEE Xplore Digital Library
Author	Trzasko, J. Manduca, A.
Copyright Year	1982
Abstract	In clinical magnetic resonance imaging (MRI), any reduction in scan time offers a number of potential benefits ranging from high-temporal-rate observation of physiological processes to improvements in patient comfort. Following recent developments in compressive sensing (CS) theory, several authors have demonstrated that certain classes of MR images which possess sparse representations in some transform domain can be accurately reconstructed from very highly undersampled K-space data by solving a convex lscr₁-minimization problem. Although lscr₁-based techniques are extremely powerful, they inherently require a degree of over-sampling above the theoretical minimum sampling rate to guarantee that exact reconstruction can be achieved. In this paper, we propose a generalization of the CS paradigm based on homotopic approximation of the lscr₀ quasi-norm and show how MR image reconstruction can be pushed even further below the Nyquist limit and significantly closer to the theoretical bound. Following a brief review of standard CS methods and the developed theoretical extensions, several example MRI reconstructions from highly undersampled K-space data are presented.
Sponsorship	IEEE Engineering in Medicine and Biology Society IEEE Nuclear and Plasma Sciences Society IEEE Signal Processing Society IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society
Page Count	16
File Size	2520557
Starting Page	106
Ending Page	121
File Format	PDF
ISSN	02780062
Volume Number	28
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance Image reconstruction Magnetic resonance imaging Image sampling Image coding Biomedical imaging Signal sampling Standards development Biological tissues Ionizing radiation nonconvex optimization Compressed sensing compressive sensing (CS) image reconstruction magnetic resonance imaging (MRI) Nonconvex Optimization Magnetic Resonance Imaging (MRI) Image Reconstruction Compressive Sensing Compressed Sensing
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications Radiological and Ultrasound Technology Software

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