基于压缩感知的MRI多分量松弛测量

M. Ambrosanio, F. Baselice, G. Ferraioli, F. Lenti, V. Pascazio
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引用次数: 0

摘要

提出了一种新的1范数最小化方法在核磁共振成像领域的应用。这种被称为体素内分析(IVA)的新方法,通过将不同的采集与标准分辨率相结合,能够研究每个成像体素内不同贡献的存在,即不同组织。该方法在某种程度上类似于光谱学,但它不是搜索不同的共振频率,而是在每个体素中区分具有不同自旋-自旋弛豫时间特征的组织。所提出的方法能够通过使用任何获取方案在全分辨率下获取MR图像。为了测试这种方法,已经建造了一个幻影和图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MRI multicomponent relaxometry based on compressive sensing
A novel application of ℓ1-norm minimization in the MRI field is presented. The novel methodology, called Intra Voxel Analysis (IVA), by combining different acquisitions with standard resolution, is able to investigate the presence of different contributions, i.e., of different tissues, inside each imaged voxel. The approach is somehow similar to spectroscopy, but instead of searching different resonance frequencies, it discriminates within each voxel the tissues characterized by different spin-spin relaxation times. The proposed methodology is able to work on MR images acquired at full resolution by using any acquisition scheme. A phantom has been built and images for testing the approach.
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