View in EDS

Isotropic multichannel total variation framework for joint reconstruction of multicontrast parallel MRI.

Saved in:
Bibliographic Details
Title: Isotropic multichannel total variation framework for joint reconstruction of multicontrast parallel MRI.
Authors: Esfahani EE; Independent Researcher, Tehran, Iran.
Source: Journal of medical imaging (Bellingham, Wash.) [J Med Imaging (Bellingham)] 2022 Jan; Vol. 9 (1), pp. 013502. Date of Electronic Publication: 2022 Feb 16.
Publication Type: Journal Article
Language: English
Journal Info: Publisher: Society of Photo-Optical Instrumentation Engineers Country of Publication: United States NLM ID: 101643461 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2329-4302 (Print) Linking ISSN: 23294302 NLM ISO Abbreviation: J Med Imaging (Bellingham) Subsets: PubMed not MEDLINE
Imprint Name(s): Original Publication: Bellingham, Wash. : Society of Photo-Optical Instrumentation Engineers
Abstract: Purpose : To develop a synergistic image reconstruction framework that exploits multicontrast (MC), multicoil, and compressed sensing (CS) redundancies in magnetic resonance imaging (MRI). Approach : CS, MC acquisition, and parallel imaging (PI) have been individually well developed, but the combination of the three has not been equally well studied, much less the potential benefits of isotropy within such a setting. Inspired by total variation theory, we introduce an isotropic MC image regularizer and attain its full potential by integrating it into compressed MC multicoil MRI. A convex optimization problem is posed to model the new variational framework and a first-order algorithm is developed to solve the problem. Results : It turns out that the proposed isotropic regularizer outperforms many of the state-of-the-art reconstruction methods not only in terms of rotation-invariance preservation of symmetrical features, but also in suppressing noise or streaking artifacts, which are normally encountered in PI methods at aggressive undersampling rates. Moreover, the new framework significantly prevents intercontrast leakage of contrast-specific details, which seems to be a difficult situation to handle for some variational and low-rank MC reconstruction approaches. Conclusions : The new framework is a viable option for image reconstruction in fast protocols of MC parallel MRI, potentially reducing patient discomfort in otherwise long and time-consuming scans.
(© 2022 Society of Photo-Optical Instrumentation Engineers (SPIE).)
References: Magn Reson Imaging. 2014 Dec;32(10):1344-52. (PMID: 25193110)
Sci Rep. 2019 Feb 28;9(1):3034. (PMID: 30816312)
IEEE Trans Med Imaging. 2014 Mar;33(3):668-81. (PMID: 24595341)
IEEE Trans Image Process. 1998;7(3):304-9. (PMID: 18276250)
Radiographics. 2005 Sep-Oct;25(5):1279-97. (PMID: 16160112)
Magn Reson Med. 2016 Apr;75(4):1499-514. (PMID: 25952136)
Magn Reson Med. 2018 Aug;80(2):619-632. (PMID: 29322551)
Magn Reson Med. 2011 Dec;66(6):1601-15. (PMID: 21671267)
Magn Reson Med. 2002 Jun;47(6):1202-10. (PMID: 12111967)
Phys Med Biol. 2015 Mar 7;60(5):1741-62. (PMID: 25658985)
Magn Reson Med. 2017 Mar;77(3):1021-1035. (PMID: 27037836)
IEEE Trans Med Imaging. 2020 Mar;39(3):621-633. (PMID: 31395541)
IEEE Trans Med Imaging. 2017 Jan;36(1):1-16. (PMID: 28055827)
Magn Reson Med. 2011 Feb;65(2):480-91. (PMID: 21264937)
IEEE Trans Pattern Anal Mach Intell. 1986 Jun;8(6):679-98. (PMID: 21869365)
Magn Reson Med. 1999 Nov;42(5):952-62. (PMID: 10542355)
Magn Reson Imaging. 2020 Sep;71:80-92. (PMID: 32302736)
Magn Reson Imaging. 2016 Oct;34(8):1161-70. (PMID: 27262829)
Magn Reson Med. 2014 Mar;71(3):990-1001. (PMID: 23649942)
NMR Biomed. 2020 Apr;33(4):e4247. (PMID: 31970849)
Med Image Anal. 2016 Jan;27:93-104. (PMID: 26096982)
Magn Reson Med. 2014 Oct;72(4):959-70. (PMID: 24248734)
BMC Med Imaging. 2018 May 3;18(1):7. (PMID: 29724180)
Med Image Anal. 2020 Jul;63:101687. (PMID: 32294605)
Contributed Indexing: Keywords: compressed sensing; iterative image reconstruction; magnetic resonance imaging; multicontrast imaging; parallel imaging; variational image processing
Entry Date(s): Date Created: 20220221 Latest Revision: 20230217
Update Code: 20250114
PubMed Central ID: PMC8849322
DOI: 10.1117/1.JMI.9.1.013502
PMID: 35187198
Database: MEDLINE
Description
Abstract:Purpose : To develop a synergistic image reconstruction framework that exploits multicontrast (MC), multicoil, and compressed sensing (CS) redundancies in magnetic resonance imaging (MRI). Approach : CS, MC acquisition, and parallel imaging (PI) have been individually well developed, but the combination of the three has not been equally well studied, much less the potential benefits of isotropy within such a setting. Inspired by total variation theory, we introduce an isotropic MC image regularizer and attain its full potential by integrating it into compressed MC multicoil MRI. A convex optimization problem is posed to model the new variational framework and a first-order algorithm is developed to solve the problem. Results : It turns out that the proposed isotropic regularizer outperforms many of the state-of-the-art reconstruction methods not only in terms of rotation-invariance preservation of symmetrical features, but also in suppressing noise or streaking artifacts, which are normally encountered in PI methods at aggressive undersampling rates. Moreover, the new framework significantly prevents intercontrast leakage of contrast-specific details, which seems to be a difficult situation to handle for some variational and low-rank MC reconstruction approaches. Conclusions : The new framework is a viable option for image reconstruction in fast protocols of MC parallel MRI, potentially reducing patient discomfort in otherwise long and time-consuming scans.<br /> (© 2022 Society of Photo-Optical Instrumentation Engineers (SPIE).)
ISSN:2329-4302
DOI:10.1117/1.JMI.9.1.013502