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用于加速磁共振指纹成像采集的稳健滑动窗口重建。

Robust sliding-window reconstruction for Accelerating the acquisition of MR fingerprinting.

机构信息

Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.

Center for Innovative and Collaborative Detection and Treatment of Infectious Diseases, Zhejiang University, Hangzhou, Zhejiang, China.

出版信息

Magn Reson Med. 2017 Oct;78(4):1579-1588. doi: 10.1002/mrm.26521. Epub 2016 Nov 7.

Abstract

PURPOSE

To develop a method for accelerated and robust MR fingerprinting (MRF) with improved image reconstruction and parameter matching processes.

THEORY AND METHODS

A sliding-window (SW) strategy was applied to MRF, in which signal and dictionary matching was conducted between fingerprints consisting of mixed-contrast image series reconstructed from consecutive data frames segmented by a sliding window, and a precalculated mixed-contrast dictionary. The effectiveness and performance of this new method, dubbed SW-MRF, was evaluated in both phantom and in vivo. Error quantifications were conducted on results obtained with various settings of SW reconstruction parameters.

RESULTS

Compared with the original MRF strategy, the results of both phantom and in vivo experiments demonstrate that the proposed SW-MRF strategy either provided similar accuracy with reduced acquisition time, or improved accuracy with equal acquisition time. Parametric maps of T , T , and proton density of comparable quality could be achieved with a two-fold or more reduction in acquisition time. The effect of sliding-window width on dictionary sensitivity was also estimated.

CONCLUSION

The novel SW-MRF recovers high quality image frames from highly undersampled MRF data, which enables more robust dictionary matching with reduced numbers of data frames. This time efficiency may facilitate MRF applications in time-critical clinical settings. Magn Reson Med 78:1579-1588, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

摘要

目的

开发一种用于加速和稳健磁共振指纹识别(MRF)的方法,该方法具有改进的图像重建和参数匹配过程。

理论与方法

将滑动窗口(SW)策略应用于 MRF,其中信号和字典匹配是在由滑动窗口分段的连续数据帧重建的混合对比度图像序列组成的指纹之间进行的,以及预计算的混合对比度字典。该新方法(称为 SW-MRF)在体模和体内的有效性和性能进行了评估。对各种 SW 重建参数设置下获得的结果进行了误差量化。

结果

与原始 MRF 策略相比,体模和体内实验的结果表明,所提出的 SW-MRF 策略要么以降低采集时间提供相似的准确性,要么以相等的采集时间提高准确性。可以将采集时间减少两倍或更多,从而获得具有可比质量的 T 、 T 、质子密度的参数图。还估计了滑动窗口宽度对字典灵敏度的影响。

结论

新颖的 SW-MRF 从高度欠采样的 MRF 数据中恢复高质量的图像帧,从而可以通过减少数据帧数来实现更稳健的字典匹配。这种时间效率可能会促进 MRF 在时间关键的临床环境中的应用。磁共振医学杂志 78:1579-1588,2017. © 2016 国际磁共振学会。

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