NDLI: Local error detection in sparse magnetic resonance imaging

Content Provider	IEEE Xplore Digital Library
Author	Singh, V. Tewfik, A.H.
Copyright Year	2013
Description	Author affiliation: Univ. of Texas at Austin, Austin, TX, USA (Singh, V.; Tewfik, A.H.)
Abstract	Due to the physical and the physiological constraints, the sparse magnetic resonance imaging (MRI) techniques operate in a regime where the theoretical guarantees of compressed sensing for recovery with high fidelity are improbable. Thus, the effective signal encoding in sparse MRI techniques is lossy, even at low acceleration factors. For widespread clinical use of sparse MRI, following two problems are proposed: 1) detection of errors in sparse recovered images and, 2) localized and highly fast acquisition of lossless image information in regions with high errors. This paper focuses on the former problem of detecting erroneously recovered image regions and proposes a solution based on joint statistics of wavelet coefficients across multiple subbands. The proposed technique uses multivariate generalized Gaussian distributions to jointly model the wavelet coefficients for all local regions conforming to a unique boundary signature in the image. Detection of local errors is formulated as measuring the degree of variation in the joint statistical model for boundary signatures between the recovered image and a training image. The training image can be a single Nyquist sampled image acquired prior to or during the sparse MRI volumetric scan. The preliminary experimental results show good conformance of the proposed method in detecting local error regions. The high error regions are detected with an accuracy of (91.8±1.6)% at (29.2±4.7)% false detection rate for acceleration factors up to 4.
Starting Page	957
Ending Page	960
File Size	837407
Page Count	4
File Format	PDF
ISBN	9781479902484
DOI	10.1109/GlobalSIP.2013.6737051
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Magnetic Resonance Imaging Accuracy Abstracts Compressed Sensing Sparse Representations Steerable Pyramids Indexes Generalized Gaussian Distributions
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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