Joint Reconstruction of Multi-contrast Images and Multi-channel Coil Sensitivities

Zhongzhou Chen, Yanan Ren, Shi Su, Caiyun Shi, Jim Ji, Hairong Zheng, Xin Liu, Guoxi Xie

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Magnetic resonance imaging (MRI) has an important feature that it provides multiple images with different contrasts for complementary diagnostic information. However, a large amount of data is needed for multi-contrast images depiction, and thus, the scan is time-consuming. Many methods based on parallel magnetic resonance imaging (pMRI) and compressed sensing (CS) are applied to accelerate multi-contrast MR imaging. Nevertheless, the image reconstructed by sophisticated pMRI methods contains residual aliasing artifact that degrades the quality of the image when the acceleration factor is high. Other methods based on CS always suffer the regularization parameter-selecting problem. To address these issues, a new method is presented for joint multi-contrast image reconstruction and coil sensitivity estimation. The coil sensitivities can be shared during the reconstruction due to the identity of coil sensitivity profiles of different contrast images for imaging stationary tissues. The proposed method uses the coil sensitivities as sharable information during the reconstruction to improve the reconstruction quality. As a result, the residual aliasing artifact can be effectively removed in the reconstructed multi-contrast images even if the acceleration factor is high. Besides, as there is no regularization term in the proposed method, the troublesome regularization parameter selection in the CS can also be avoided. Results from multi-contrast in vivo experiments demonstrated that multi-contrast images can be jointly reconstructed by the proposed method with effective removal of the residual aliasing artifact at a high acceleration factor.

Original languageEnglish
Pages (from-to)955-969
Number of pages15
JournalApplied Magnetic Resonance
Volume48
Issue number9
DOIs
Publication statusPublished - 1 Sep 2017

Fingerprint

image contrast
coils
magnetic resonance
artifacts
sensitivity
high acceleration
image reconstruction
profiles

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

Cite this

Joint Reconstruction of Multi-contrast Images and Multi-channel Coil Sensitivities. / Chen, Zhongzhou; Ren, Yanan; Su, Shi; Shi, Caiyun; Ji, Jim; Zheng, Hairong; Liu, Xin; Xie, Guoxi.

In: Applied Magnetic Resonance, Vol. 48, No. 9, 01.09.2017, p. 955-969.

Research output: Contribution to journalArticle

Chen, Zhongzhou ; Ren, Yanan ; Su, Shi ; Shi, Caiyun ; Ji, Jim ; Zheng, Hairong ; Liu, Xin ; Xie, Guoxi. / Joint Reconstruction of Multi-contrast Images and Multi-channel Coil Sensitivities. In: Applied Magnetic Resonance. 2017 ; Vol. 48, No. 9. pp. 955-969.
@article{4c8fd8f9040b4de3b084fc76ff3e3732,
title = "Joint Reconstruction of Multi-contrast Images and Multi-channel Coil Sensitivities",
abstract = "Magnetic resonance imaging (MRI) has an important feature that it provides multiple images with different contrasts for complementary diagnostic information. However, a large amount of data is needed for multi-contrast images depiction, and thus, the scan is time-consuming. Many methods based on parallel magnetic resonance imaging (pMRI) and compressed sensing (CS) are applied to accelerate multi-contrast MR imaging. Nevertheless, the image reconstructed by sophisticated pMRI methods contains residual aliasing artifact that degrades the quality of the image when the acceleration factor is high. Other methods based on CS always suffer the regularization parameter-selecting problem. To address these issues, a new method is presented for joint multi-contrast image reconstruction and coil sensitivity estimation. The coil sensitivities can be shared during the reconstruction due to the identity of coil sensitivity profiles of different contrast images for imaging stationary tissues. The proposed method uses the coil sensitivities as sharable information during the reconstruction to improve the reconstruction quality. As a result, the residual aliasing artifact can be effectively removed in the reconstructed multi-contrast images even if the acceleration factor is high. Besides, as there is no regularization term in the proposed method, the troublesome regularization parameter selection in the CS can also be avoided. Results from multi-contrast in vivo experiments demonstrated that multi-contrast images can be jointly reconstructed by the proposed method with effective removal of the residual aliasing artifact at a high acceleration factor.",
author = "Zhongzhou Chen and Yanan Ren and Shi Su and Caiyun Shi and Jim Ji and Hairong Zheng and Xin Liu and Guoxi Xie",
year = "2017",
month = "9",
day = "1",
doi = "10.1007/s00723-017-0919-4",
language = "English",
volume = "48",
pages = "955--969",
journal = "Applied Magnetic Resonance",
issn = "0937-9347",
publisher = "Springer Wien",
number = "9",

}

TY - JOUR

T1 - Joint Reconstruction of Multi-contrast Images and Multi-channel Coil Sensitivities

AU - Chen, Zhongzhou

AU - Ren, Yanan

AU - Su, Shi

AU - Shi, Caiyun

AU - Ji, Jim

AU - Zheng, Hairong

AU - Liu, Xin

AU - Xie, Guoxi

PY - 2017/9/1

Y1 - 2017/9/1

N2 - Magnetic resonance imaging (MRI) has an important feature that it provides multiple images with different contrasts for complementary diagnostic information. However, a large amount of data is needed for multi-contrast images depiction, and thus, the scan is time-consuming. Many methods based on parallel magnetic resonance imaging (pMRI) and compressed sensing (CS) are applied to accelerate multi-contrast MR imaging. Nevertheless, the image reconstructed by sophisticated pMRI methods contains residual aliasing artifact that degrades the quality of the image when the acceleration factor is high. Other methods based on CS always suffer the regularization parameter-selecting problem. To address these issues, a new method is presented for joint multi-contrast image reconstruction and coil sensitivity estimation. The coil sensitivities can be shared during the reconstruction due to the identity of coil sensitivity profiles of different contrast images for imaging stationary tissues. The proposed method uses the coil sensitivities as sharable information during the reconstruction to improve the reconstruction quality. As a result, the residual aliasing artifact can be effectively removed in the reconstructed multi-contrast images even if the acceleration factor is high. Besides, as there is no regularization term in the proposed method, the troublesome regularization parameter selection in the CS can also be avoided. Results from multi-contrast in vivo experiments demonstrated that multi-contrast images can be jointly reconstructed by the proposed method with effective removal of the residual aliasing artifact at a high acceleration factor.

AB - Magnetic resonance imaging (MRI) has an important feature that it provides multiple images with different contrasts for complementary diagnostic information. However, a large amount of data is needed for multi-contrast images depiction, and thus, the scan is time-consuming. Many methods based on parallel magnetic resonance imaging (pMRI) and compressed sensing (CS) are applied to accelerate multi-contrast MR imaging. Nevertheless, the image reconstructed by sophisticated pMRI methods contains residual aliasing artifact that degrades the quality of the image when the acceleration factor is high. Other methods based on CS always suffer the regularization parameter-selecting problem. To address these issues, a new method is presented for joint multi-contrast image reconstruction and coil sensitivity estimation. The coil sensitivities can be shared during the reconstruction due to the identity of coil sensitivity profiles of different contrast images for imaging stationary tissues. The proposed method uses the coil sensitivities as sharable information during the reconstruction to improve the reconstruction quality. As a result, the residual aliasing artifact can be effectively removed in the reconstructed multi-contrast images even if the acceleration factor is high. Besides, as there is no regularization term in the proposed method, the troublesome regularization parameter selection in the CS can also be avoided. Results from multi-contrast in vivo experiments demonstrated that multi-contrast images can be jointly reconstructed by the proposed method with effective removal of the residual aliasing artifact at a high acceleration factor.

UR - http://www.scopus.com/inward/record.url?scp=85026901509&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85026901509&partnerID=8YFLogxK

U2 - 10.1007/s00723-017-0919-4

DO - 10.1007/s00723-017-0919-4

M3 - Article

AN - SCOPUS:85026901509

VL - 48

SP - 955

EP - 969

JO - Applied Magnetic Resonance

JF - Applied Magnetic Resonance

SN - 0937-9347

IS - 9

ER -