基于主成分迭代支集检测的多对比度 磁共振快速成像

很多磁共振成像应用(如 T1、T2 参数成像)需要连续采集一系列不同对比度的图像。丰富的对比度机制反映了 人体组织的内在特性，为临床提供了有效的定量诊断手段。然而，由于扫描时间过长，这种方法在临床上的应用受到一 定的限制。近几年兴起的压缩感知理论在磁共振快速成像方面显示了巨大的潜能。其中，学者们提出一种基于主成分分 析的快速磁共振成像方法。该方法从已知的解析物理模型和参数范围中训练主成分，并通过截断的方式利用图像序列的 时域稀疏性。但是，当这种截断先验信息不准确时，上述方法可能会产生模型误差。 本文通过采用迭代支集检测的方法 实现主成分系数支集的适应性估计。文章最后通过两组人体膝盖数据的重建实验，验证了该方法的有效性。

Accelerating T2 Mapping using ISD in the Spatial-PCA Domain

A series of multi-contrast MR images are usually required in various MR applications, such as T1 and T2 mappings, which provide quantitative information of inherent tissue properties for diagnosis purpose. However, its clinical application is limited by the long scanning time. The emerging theory of compressed sensing has shown great potential in accelerating MR acquisitions. Recently, a principal component analysis based method has been proposed exploiting the temporal sparsity via truncated PCs based on the knowledge of the analytic model and possible parameter range. However, it may generate model errors when such prior information is not accurate. In this work, the support of the PC coefficients were detected in a more adaptive way using iterative support detection. Reconstructions based on two knee data sets were conducted to demonstrate the effectiveness of the proposed method.