MRI Simulation-based evaluation of an efficient under-sampling approach

Compressive sampling (CS) has been commonly employed in the field of magnetic resonance imaging (MRI) to accurately reconstruct sparse and compressive signals. In a MR image, a large amount of encoded information focuses on the origin of the k-space. For the 2D Cartesian K-space MRI, under-sampli...

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Main Authors: Anh, Quang Tran, Tien, Anh Nguyen, Van, Tu Duong, Quang, Huy Tran, Duc, Nghia Tran, Duc, Tan Tran
Format: Article
Language:English
Published: 2020
Subjects:
MRI
Online Access:https://dlib.phenikaa-uni.edu.vn/handle/PNK/536
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spelling oai:localhost:PNK-5362022-08-17T05:54:37Z MRI Simulation-based evaluation of an efficient under-sampling approach Anh, Quang Tran Tien, Anh Nguyen Van, Tu Duong Quang, Huy Tran Duc, Nghia Tran Duc, Tan Tran MRI compressed sensing power law k-space non-linear conjugate gradient Compressive sampling (CS) has been commonly employed in the field of magnetic resonance imaging (MRI) to accurately reconstruct sparse and compressive signals. In a MR image, a large amount of encoded information focuses on the origin of the k-space. For the 2D Cartesian K-space MRI, under-sampling the frequency-encoding (kx) dimension does not affect to the acquisition time, thus, only the phase-encoding (ky) dimension can be exploited. In the traditional random under-sampling approach, it acquired Gaussian random measurements along the phaseencoding (ky) in the k-space. In this paper, we proposed a hybrid under-sampling approach; the number of measurements in (ky) is divided into two portions: 70% of the measurements are for random under-sampling and 30% are for definite under-sampling near the origin of the k-space. The numerical simulation consequences pointed out that, in the lower region of the under-sampling ratio r, both the average error and the universal image quality index of the appointed scheme are drastically improved up to 55 and 77% respectively as compared to the traditional scheme. For the first time, instead of using highly computational complexity of many advanced reconstruction techniques, a simple and efficient CS method based simulation is proposed for MRI reconstruction improvement. These findings are very useful for designing new MRI data acquisition approaches 2020-08-13T07:47:19Z 2020-08-13T07:47:19Z 2020 Article https://dlib.phenikaa-uni.edu.vn/handle/PNK/536 10.3934/mbe.2020224 en application/pdf
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic MRI
compressed sensing
power law
k-space
non-linear conjugate gradient
spellingShingle MRI
compressed sensing
power law
k-space
non-linear conjugate gradient
Anh, Quang Tran
Tien, Anh Nguyen
Van, Tu Duong
Quang, Huy Tran
Duc, Nghia Tran
Duc, Tan Tran
MRI Simulation-based evaluation of an efficient under-sampling approach
description Compressive sampling (CS) has been commonly employed in the field of magnetic resonance imaging (MRI) to accurately reconstruct sparse and compressive signals. In a MR image, a large amount of encoded information focuses on the origin of the k-space. For the 2D Cartesian K-space MRI, under-sampling the frequency-encoding (kx) dimension does not affect to the acquisition time, thus, only the phase-encoding (ky) dimension can be exploited. In the traditional random under-sampling approach, it acquired Gaussian random measurements along the phaseencoding (ky) in the k-space. In this paper, we proposed a hybrid under-sampling approach; the number of measurements in (ky) is divided into two portions: 70% of the measurements are for random under-sampling and 30% are for definite under-sampling near the origin of the k-space. The numerical simulation consequences pointed out that, in the lower region of the under-sampling ratio r, both the average error and the universal image quality index of the appointed scheme are drastically improved up to 55 and 77% respectively as compared to the traditional scheme. For the first time, instead of using highly computational complexity of many advanced reconstruction techniques, a simple and efficient CS method based simulation is proposed for MRI reconstruction improvement. These findings are very useful for designing new MRI data acquisition approaches
format Article
author Anh, Quang Tran
Tien, Anh Nguyen
Van, Tu Duong
Quang, Huy Tran
Duc, Nghia Tran
Duc, Tan Tran
author_facet Anh, Quang Tran
Tien, Anh Nguyen
Van, Tu Duong
Quang, Huy Tran
Duc, Nghia Tran
Duc, Tan Tran
author_sort Anh, Quang Tran
title MRI Simulation-based evaluation of an efficient under-sampling approach
title_short MRI Simulation-based evaluation of an efficient under-sampling approach
title_full MRI Simulation-based evaluation of an efficient under-sampling approach
title_fullStr MRI Simulation-based evaluation of an efficient under-sampling approach
title_full_unstemmed MRI Simulation-based evaluation of an efficient under-sampling approach
title_sort mri simulation-based evaluation of an efficient under-sampling approach
publishDate 2020
url https://dlib.phenikaa-uni.edu.vn/handle/PNK/536
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score 8.891145