Central Library

Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms (Record no. 76803)

000 -LEADER
fixed length control field 04057nam a22005655i 4500
001 - CONTROL NUMBER
control field 978-981-13-3597-6
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801214832.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 181229s2019 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811335976
-- 978-981-13-3597-6
082 04 - CLASSIFICATION NUMBER
Call Number 621.382
100 1# - AUTHOR NAME
Author Deka, Bhabesh.
245 10 - TITLE STATEMENT
Title Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms
Sub Title A Convex Optimization Approach /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2019.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIII, 122 p. 38 illus., 23 illus. in color.
490 1# - SERIES STATEMENT
Series statement Springer Series on Bio- and Neurosystems,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 1. Introduction to Compressed Sensing Magnetic Resonance Imaging -- 2. Compressed Sensing MRI Reconstruction Problem -- 3. Fast Algorithms for Compressed Sensing MRI Reconstruction -- 4. Simulation Results -- 5. Performance Evaluation and Benchmark Setting -- 6. Conclusions and Future Directions.
520 ## - SUMMARY, ETC.
Summary, etc This book presents a comprehensive review of the recent developments in fast L1-norm regularization-based compressed sensing (CS) magnetic resonance image reconstruction algorithms. Compressed sensing magnetic resonance imaging (CS-MRI) is able to reduce the scan time of MRI considerably as it is possible to reconstruct MR images from only a few measurements in the k-space; far below the requirements of the Nyquist sampling rate. L1-norm-based regularization problems can be solved efficiently using the state-of-the-art convex optimization techniques, which in general outperform the greedy techniques in terms of quality of reconstructions. Recently, fast convex optimization based reconstruction algorithms have been developed which are also able to achieve the benchmarks for the use of CS-MRI in clinical practice. This book enables graduate students, researchers, and medical practitioners working in the field of medical image processing, particularly in MRI to understand the need for the CS in MRI, and thereby how it could revolutionize the soft tissue imaging to benefit healthcare technology without making major changes in the existing scanner hardware. It would be particularly useful for researchers who have just entered into the exciting field of CS-MRI and would like to quickly go through the developments to date without diving into the detailed mathematical analysis. Finally, it also discusses recent trends and future research directions for implementation of CS-MRI in clinical practice, particularly in Bio- and Neuro-informatics applications.
700 1# - AUTHOR 2
Author 2 Datta, Sumit.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-13-3597-6
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
100 1# - AUTHOR NAME
-- (orcid)0000-0002-9679-6159
-- https://orcid.org/0000-0002-9679-6159
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2019.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Biomedical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Radiology.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Speech and Image Processing .
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Biomedical Engineering and Bioengineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Radiology.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2520-8543 ;
912 ## -
-- ZDB-2-ENG
912 ## -
-- ZDB-2-SXE

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