Segmented Multistage Reconstruction of Magnetic Resonance Images

Compressed sensing of magnetic resonance imaging refers to the reconstruction of magnetic resonance images from partially sampled k-space data. The k-space data reduces reconstruction processing time but at the cost of increasing artifacts - especially with the higher reduction factor of the raw d...

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Autores principales:	FARIS, M., JAVID, T., KAZMI, M., AZIZ, A.
Formato:	article
Lenguaje:	EN
Publicado:	Stefan cel Mare University of Suceava 2021
Materias:	compressed sensing fourier transforms image reconstruction magnetic resonance imaging spatial resolution Electrical engineering. Electronics. Nuclear engineering TK1-9971 Computer engineering. Computer hardware TK7885-7895
Acceso en línea:	https://doaj.org/article/aac77549b3884519b556731476a62245
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id	oai:doaj.org-article:aac77549b3884519b556731476a62245
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spelling	oai:doaj.org-article:aac77549b3884519b556731476a622452021-12-05T17:03:49ZSegmented Multistage Reconstruction of Magnetic Resonance Images1582-74451844-760010.4316/AECE.2021.04012https://doaj.org/article/aac77549b3884519b556731476a622452021-11-01T00:00:00Zhttp://dx.doi.org/10.4316/AECE.2021.04012https://doaj.org/toc/1582-7445https://doaj.org/toc/1844-7600Compressed sensing of magnetic resonance imaging refers to the reconstruction of magnetic resonance images from partially sampled k-space data. The k-space data reduces reconstruction processing time but at the cost of increasing artifacts - especially with the higher reduction factor of the raw data. This work proposes a segmented region-based reconstruction technique to reduce image artifacts with enhanced quality and high temporal resolution. The proposed method segments partially sampled k-space data in two segments according to their frequencies. Lower frequency components at the central region are selected and predicted using nuclear norm minimization. This part and the peripheral part of the k-space components at higher frequencies are merged. The recovery technique iterates to reconstruct more accurate images in terms of conventional compressed sensing techniques. The performance of the proposed method is evaluated and compared with compressed sensing, two-stage compressed sensing, and modified total variation technique. Better results in term of normalized mean square error NMSE, reconstruction time and structural similarity index measure SSIM show the effectiveness of the proposed method with a high reduction factor of data.FARIS, M.JAVID, T.KAZMI, M.AZIZ, A.Stefan cel Mare University of Suceavaarticlecompressed sensingfourier transformsimage reconstructionmagnetic resonance imagingspatial resolutionElectrical engineering. Electronics. Nuclear engineeringTK1-9971Computer engineering. Computer hardwareTK7885-7895ENAdvances in Electrical and Computer Engineering, Vol 21, Iss 4, Pp 107-114 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	compressed sensing fourier transforms image reconstruction magnetic resonance imaging spatial resolution Electrical engineering. Electronics. Nuclear engineering TK1-9971 Computer engineering. Computer hardware TK7885-7895
spellingShingle	compressed sensing fourier transforms image reconstruction magnetic resonance imaging spatial resolution Electrical engineering. Electronics. Nuclear engineering TK1-9971 Computer engineering. Computer hardware TK7885-7895 FARIS, M. JAVID, T. KAZMI, M. AZIZ, A. Segmented Multistage Reconstruction of Magnetic Resonance Images
description	Compressed sensing of magnetic resonance imaging refers to the reconstruction of magnetic resonance images from partially sampled k-space data. The k-space data reduces reconstruction processing time but at the cost of increasing artifacts - especially with the higher reduction factor of the raw data. This work proposes a segmented region-based reconstruction technique to reduce image artifacts with enhanced quality and high temporal resolution. The proposed method segments partially sampled k-space data in two segments according to their frequencies. Lower frequency components at the central region are selected and predicted using nuclear norm minimization. This part and the peripheral part of the k-space components at higher frequencies are merged. The recovery technique iterates to reconstruct more accurate images in terms of conventional compressed sensing techniques. The performance of the proposed method is evaluated and compared with compressed sensing, two-stage compressed sensing, and modified total variation technique. Better results in term of normalized mean square error NMSE, reconstruction time and structural similarity index measure SSIM show the effectiveness of the proposed method with a high reduction factor of data.
format	article
author	FARIS, M. JAVID, T. KAZMI, M. AZIZ, A.
author_facet	FARIS, M. JAVID, T. KAZMI, M. AZIZ, A.
author_sort	FARIS, M.
title	Segmented Multistage Reconstruction of Magnetic Resonance Images
title_short	Segmented Multistage Reconstruction of Magnetic Resonance Images
title_full	Segmented Multistage Reconstruction of Magnetic Resonance Images
title_fullStr	Segmented Multistage Reconstruction of Magnetic Resonance Images
title_full_unstemmed	Segmented Multistage Reconstruction of Magnetic Resonance Images
title_sort	segmented multistage reconstruction of magnetic resonance images
publisher	Stefan cel Mare University of Suceava
publishDate	2021
url	https://doaj.org/article/aac77549b3884519b556731476a62245
work_keys_str_mv	AT farism segmentedmultistagereconstructionofmagneticresonanceimages AT javidt segmentedmultistagereconstructionofmagneticresonanceimages AT kazmim segmentedmultistagereconstructionofmagneticresonanceimages AT aziza segmentedmultistagereconstructionofmagneticresonanceimages
_version_	1718371256937480192

Segmented Multistage Reconstruction of Magnetic Resonance Images

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