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A Matlab-Based Advance MR Image Reconstruction Package with Interactive Graphical User Interface

机译:基于Matlab的具有交互式图形用户界面的Advance MR图像重建软件包

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摘要

Parallel magnetic resonance imaging (PMRI) has the potential to reduce the MRI scan time by acquiring fewer k-space lines using multiple independent receiver coils instead of a single coil for data acquisition. Many advance reconstruction algorithms have been proposed in the recent past to reconstruct fully sampled images from these undersampled data. These algorithms are mainly categorized into k-space and image domain methods. The work presented in this paper develops an interactive graphical user interface (GUI) tool for a variety of advance reconstruction algorithms in MRI, namely, sensitivity encoding (SENSE) [1], conjugate gradient SENSE (CG-SENSE) [2], compressed sensing [3], and radial GRAPPA algorithms [4-7]. The proposed GUI tool environment is a multiple window interface developed using MATLAB (R2013a). The user has the option of loading the undersampled data in an interactive fashion, and image reconstruction can be performed using any of the available algorithms. The quality of the reconstructed images is evaluated using artifact power (AP) and SNR maps. This interactive platform is aimed at providing the researchers and medical practitioners an easy and interactive tool to test their data using various advance reconstruction algorithms in MRI.
机译:并行磁共振成像(PMRI)有潜力通过使用多个独立的接收器线圈而不是单个线圈进行数据采集来采集更少的k空间线来减少MRI扫描时间。最近提出了许多先进的重建算法,以从这些欠采样数据重建完全采样的图像。这些算法主要分为k空间和图像域方法。本文介绍的工作为MRI中的各种高级重建算法开发了一种交互式图形用户界面(GUI)工具,即敏感性编码(SENSE)[1],共轭梯度SENSE(CG-SENSE)[2],压缩感应[3]和径向GRAPPA算法[4-7]。所建议的GUI工具环境是使用MATLAB(R2013a)开发的多窗口界面。用户可以选择以交互方式加载欠采样数据,并且可以使用任何可用算法来执行图像重建。使用伪影功率(AP)和SNR映射图评估重建图像的质量。这个交互式平台旨在为研究人员和医学从业者提供一种简便而交互式的工具,以使用各种先进的MRI重建算法测试其数据。

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