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首页> 外文期刊>Medical image analysis >Image reconstruction of compressed sensing MRI using graph-based redundant wavelet transform
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Image reconstruction of compressed sensing MRI using graph-based redundant wavelet transform

机译：基于图的冗余小波变换的压缩感知MRI图像重建

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摘要

Compressed sensing magnetic resonance imaging has shown great capacity for accelerating magnetic resonance imaging if an image can be sparsely represented. How the image is sparsified seriously affects its reconstruction quality. In the present study, a graph-based redundant wavelet transform is introduced to sparsely represent magnetic resonance images in iterative image reconstructions. With this transform, image patches is viewed as vertices and their differences as edges, and the shortest path on the graph minimizes the total difference of all image patches. Using the l(1) norm regularized formulation of the problem solved by an alternating-direction minimization with continuation algorithm, the experimental results demonstrate that the proposed method outperforms several state-of-the-art reconstruction methods in removing artifacts and achieves fewer reconstruction errors on the tested datasets. (C) 2015 Elsevier B.V. All rights reserved.
机译：如果可以稀疏表示图像，则压缩感测磁共振成像已经显示出极大的加速磁共振成像的能力。图像的稀疏程度严重影响其重建质量。在本研究中，引入了基于图的冗余小波变换来在迭代图像重建中稀疏表示磁共振图像。通过此变换，图像块被视为顶点，而它们的差异被视为边缘，并且图形上的最短路径将所有图像块的总差异最小化。使用采用交替方向最小化和连续算法解决的问题的l（1）范式正规化公式，实验结果表明，该方法在去除伪影方面优于几种最新的重建方法，并且重建错误更少在测试的数据集上。 （C）2015 Elsevier B.V.保留所有权利。

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