一种用于复值MRI重建的改进相位循环方法。

IF 3.3 Q2 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Imaging Pub Date : 2020-11-18 eCollection Date: 2020-01-01 DOI:10.1155/2020/8846220
Wei He, Yu Zhang, Junling Ding, Linman Zhao
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引用次数: 1

摘要

相位循环法是目前最先进的复值磁共振图像重建方法。然而,当它遵循实际的二维(2D)子采样笛卡尔采集时,它只在相位编码方向强制随机采样,出现了一些幅度上的伪影。提出了一种改进的方法,通过在相位循环方法中加入一维总变差(TV)正则化,在幅度分量更新之前对其进行“预处理”,从而在实际MRI子采样中去除这些伪影。此外,采用了SFISTA中使用的一种操作来更新幅值和相位图像,以获得更好的解。实验结果表明,该方法能够有效地消除环形伪影,提高图像的震级重建效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Modified Phase Cycling Method for Complex-Valued MRI Reconstruction.

A Modified Phase Cycling Method for Complex-Valued MRI Reconstruction.

A Modified Phase Cycling Method for Complex-Valued MRI Reconstruction.

A Modified Phase Cycling Method for Complex-Valued MRI Reconstruction.

The phase cycling method is a state-of-the-art method to reconstruct complex-valued MR image. However, when it follows practical two-dimensional (2D) subsampling Cartesian acquisition which is only enforcing random sampling in the phase-encoding direction, a number of artifacts in magnitude appear. A modified approach is proposed to remove these artifacts under practical MRI subsampling, by adding one-dimensional total variation (TV) regularization into the phase cycling method to "pre-process" the magnitude component before its update. Furthermore, an operation used in SFISTA is employed to update the magnitude and phase images for better solutions. The results of the experiments show the ability of the proposed method to eliminate the ring artifacts and improve the magnitude reconstruction.

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来源期刊
CiteScore
12.00
自引率
0.00%
发文量
11
审稿时长
20 weeks
期刊介绍: The International Journal of Biomedical Imaging is managed by a board of editors comprising internationally renowned active researchers. The journal is freely accessible online and also offered for purchase in print format. It employs a web-based review system to ensure swift turnaround times while maintaining high standards. In addition to regular issues, special issues are organized by guest editors. The subject areas covered include (but are not limited to): Digital radiography and tomosynthesis X-ray computed tomography (CT) Magnetic resonance imaging (MRI) Single photon emission computed tomography (SPECT) Positron emission tomography (PET) Ultrasound imaging Diffuse optical tomography, coherence, fluorescence, bioluminescence tomography, impedance tomography Neutron imaging for biomedical applications Magnetic and optical spectroscopy, and optical biopsy Optical, electron, scanning tunneling/atomic force microscopy Small animal imaging Functional, cellular, and molecular imaging Imaging assays for screening and molecular analysis Microarray image analysis and bioinformatics Emerging biomedical imaging techniques Imaging modality fusion Biomedical imaging instrumentation Biomedical image processing, pattern recognition, and analysis Biomedical image visualization, compression, transmission, and storage Imaging and modeling related to systems biology and systems biomedicine Applied mathematics, applied physics, and chemistry related to biomedical imaging Grid-enabling technology for biomedical imaging and informatics
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