NDLI: Joint recovery of under sampled signals on a manifold: Application to free breathing cardiac MRI

Content Provider	IEEE Xplore Digital Library
Author	Poddar, S. Lingala, S.G. Jacob, M.
Copyright Year	2014
Description	Author affiliation: Univ. of Iowa, Iowa City, IA, USA (Poddar, S.; Lingala, S.G.; Jacob, M.)
Abstract	We introduce novel algorithms for the joint recovery of an ensemble of signals that live on a smooth manifold from their under sampled measurements. Unlike current methods that are designed to recover a single signal assuming perfect knowledge of the manifold model, the proposed algorithms exploit similarity between the signals without prior knowledge of the underlying manifold structure. Our first algorithm is a two-step scheme, where the Laplacian of the graph associated with the manifold is estimated from similar under sampled measurements made on the signals; this Laplacian is used to formulate the problem as a penalized optimization scheme, where smoothness of the signals on the manifold is chosen as the penalty. The second algorithm is an iterative scheme that alternates between computation of the Laplacian and the signals. Validation of the proposed algorithms using simulations and experimental MRI data demonstrate their utility in accelerating free breathing cardiac MRI.
Sponsorship	IEEE Signal Process. Soc.
Starting Page	6904
Ending Page	6908
File Size	473145
Page Count	5
File Format	PDF
ISBN	9781479928934
DOI	10.1109/ICASSP.2014.6854938
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-04
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	free breathing cardiac MRI manifolds compressive sensing cine
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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