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通过数据欠采样和压缩感知重建减少临床磁共振成像中的采集时间。

Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction.

作者信息

Hollingsworth Kieren Grant

机构信息

Newcastle Magnetic Resonance Centre, Institute of Cellular Medicine, Newcastle University, NE 4 5PL, UK.

出版信息

Phys Med Biol. 2015 Nov 7;60(21):R297-322. doi: 10.1088/0031-9155/60/21/R297. Epub 2015 Oct 8.

Abstract

MRI is often the most sensitive or appropriate technique for important measurements in clinical diagnosis and research, but lengthy acquisition times limit its use due to cost and considerations of patient comfort and compliance. Once an image field of view and resolution is chosen, the minimum scan acquisition time is normally fixed by the amount of raw data that must be acquired to meet the Nyquist criteria. Recently, there has been research interest in using the theory of compressed sensing (CS) in MR imaging to reduce scan acquisition times. The theory argues that if our target MR image is sparse, having signal information in only a small proportion of pixels (like an angiogram), or if the image can be mathematically transformed to be sparse then it is possible to use that sparsity to recover a high definition image from substantially less acquired data. This review starts by considering methods of k-space undersampling which have already been incorporated into routine clinical imaging (partial Fourier imaging and parallel imaging), and then explains the basis of using compressed sensing in MRI. The practical considerations of applying CS to MRI acquisitions are discussed, such as designing k-space undersampling schemes, optimizing adjustable parameters in reconstructions and exploiting the power of combined compressed sensing and parallel imaging (CS-PI). A selection of clinical applications that have used CS and CS-PI prospectively are considered. The review concludes by signposting other imaging acceleration techniques under present development before concluding with a consideration of the potential impact and obstacles to bringing compressed sensing into routine use in clinical MRI.

摘要

在临床诊断和研究中,磁共振成像(MRI)通常是进行重要测量时最敏感或最合适的技术,但由于成本以及对患者舒适度和依从性的考虑,较长的采集时间限制了其应用。一旦选定图像视野和分辨率,通常最小扫描采集时间由为满足奈奎斯特准则而必须采集的原始数据量确定。最近,在磁共振成像中利用压缩感知(CS)理论来减少扫描采集时间引起了研究兴趣。该理论认为,如果我们的目标磁共振图像是稀疏的,即仅在一小部分像素中具有信号信息(如血管造影),或者如果图像可以通过数学变换变得稀疏,那么就有可能利用这种稀疏性从大大减少的采集数据中恢复高清图像。本综述首先考虑已纳入常规临床成像的k空间欠采样方法(部分傅里叶成像和平行成像),然后解释在MRI中使用压缩感知的基础。讨论了将CS应用于MRI采集的实际考虑因素,例如设计k空间欠采样方案、优化重建中的可调参数以及利用压缩感知与平行成像相结合(CS-PI)的优势。考虑了一些前瞻性地使用CS和CS-PI的临床应用。综述最后指出了目前正在开发的其他成像加速技术,最后考虑了将压缩感知引入临床MRI常规使用的潜在影响和障碍。

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